Features description.
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These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\\n\\n\\n\\n\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\nInitially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\nThese books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
\n\n\n\n\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"6000",leadTitle:null,fullTitle:"Accounting and Corporate Reporting - Today and Tomorrow",title:"Accounting and Corporate Reporting",subtitle:"Today and Tomorrow",reviewType:"peer-reviewed",abstract:'We have spent a great deal of time on the continued development of accounting and auditing standards, which are used as a primary component of corporate reporting, to reach today\'s financial reporting framework. However, is it possible to say that, currently, financial statements provide full and prompt disclosure? Or will they still be useful as a primary element with their current structures in corporate reporting? Undoubtedly, we are deeply concerned about these issues in recent times. This volume contains chapters to discuss the today\'s and tomorrow\'s accounting and corporate reporting phenomena in a comprehensive and multidimensional way. Therefore, this book is organized into six sections: "Achieving Sustainability through Corporate Reporting", "International Standardization", "Financial Reporting Quality", "Accounting Profession and Behavioral Aspects", "Public Sector Accounting and Reporting", and "Managerial Accounting".',isbn:"978-953-51-3550-0",printIsbn:"978-953-51-3549-4",pdfIsbn:"978-953-51-4651-3",doi:"10.5772/66609",price:139,priceEur:155,priceUsd:179,slug:"accounting-and-corporate-reporting-today-and-tomorrow",numberOfPages:340,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"aa4f840bdfa861be2f1c4b982a1e2cb5",bookSignature:"Soner Gokten",publishedDate:"September 20th 2017",coverURL:"https://cdn.intechopen.com/books/images_new/6000.jpg",numberOfDownloads:39022,numberOfWosCitations:7,numberOfCrossrefCitations:21,numberOfCrossrefCitationsByBook:2,numberOfDimensionsCitations:28,numberOfDimensionsCitationsByBook:2,hasAltmetrics:1,numberOfTotalCitations:56,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 24th 2016",dateEndSecondStepPublish:"December 22nd 2016",dateEndThirdStepPublish:"March 13th 2017",dateEndFourthStepPublish:"June 11th 2017",dateEndFifthStepPublish:"August 10th 2017",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"70354",title:"Ph.D.",name:"Soner",middleName:null,surname:"Gokten",slug:"soner-gokten",fullName:"Soner Gokten",profilePictureURL:"https://mts.intechopen.com/storage/users/70354/images/2275_n.jpg",biography:"Dr. Gokten is an Assistant Professor at Department of Management - Faculty of Economics and Administrative Sciences, Baskent University, Ankara, Turkey. He received his BSBA form Faculty of Economics and Administrative Sciences-Baskent University-Ankara, Turkey, MBA Finance and Ph.D. in Accounting and Finance degrees from Graduate School of Social Sciences-Gazi University, Ankara Turkey. He has published several articles, books, book chapters and conference proceedings. He is serving as a referee for national and international journals and Dr. Gokten has investment advisory, project finance and corporate valuation experience in several national and international projects.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"4",institution:{name:"Başkent University",institutionURL:null,country:{name:"Turkey"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"430",title:"Financial Reporting",slug:"financial-reporting"}],chapters:[{id:"55274",title:"Paradigm Shift in Corporate Reporting",doi:"10.5772/intechopen.68832",slug:"paradigm-shift-in-corporate-reporting",totalDownloads:2212,totalCrossrefCites:5,totalDimensionsCites:6,hasAltmetrics:0,abstract:"In this paper, we present the evolution of integrated reporting and organizations playing an active role in this process. As a result of the changes, corporate reports including only historical financial information have become insufficient. It has started to be important for the firms to be sensitive towards environment, social capital and governance. For these reasons, authorities started to search for new reporting types. Their aim was to form a report giving detailed (prospective and retrospective) information about the total performance of the firm. Sustainability reports, the starting point of integrated reporting, were established and Global Reporting Initiative (GRI) standards were formed to increase the popularization. Integrated reports aim to supply full disclosure about the firms’ strategies, goals and performances. They also respond to the demands and needs of key stakeholders. In order to actualize the financial stability and sustainability, they are necessary. Integrated reports also put related groups into play. So, decision makers become a participant instead of watching the system from outside. In addition, integrated thinking philosophy provides systematic disclosure of value creation, namely how organizations made resource allocations in the past and how they will create value in the future according to their business models.",signatures:"Pınar Okan Gökten and Beyhan Marşap",downloadPdfUrl:"/chapter/pdf-download/55274",previewPdfUrl:"/chapter/pdf-preview/55274",authors:[{id:"204188",title:"Ph.D.",name:"Pınar",surname:"Okan Gokten",slug:"pinar-okan-gokten",fullName:"Pınar Okan Gokten"},{id:"204189",title:"Prof.",name:"Beyhan",surname:"Marsap",slug:"beyhan-marsap",fullName:"Beyhan Marsap"}],corrections:null},{id:"55449",title:"Integrated Reporting: A Template for Energy Companies",doi:"10.5772/intechopen.68921",slug:"integrated-reporting-a-template-for-energy-companies",totalDownloads:2248,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Integrated reporting (IR) is an accelerated corporate reporting approach over the last few years. The idea underlying integrated reporting is to report not only on the company’s strategy, management, and financial performance, but also on its social, environmental, and economic impacts. Integrated reporting can also be defined as a holistic report aiming to present annual reports and sustainability reports in a single report, as well as short-, medium-, and long-term goals and strategies of the institution. In the integrated reporting framework prepared by the International Integrated Reporting Council (IIRC), companies aim to make company value measurable and therefore more understandable and comparable by quantifying the environmental and social implications, as well as the financial statements. In this study, firstly the conceptual framework of integrated reporting and the process of extending to integrated reporting, and then the work done in this area in Turkey were given. In the last part of this study, energy companies which are very important in the world trade and which are coming to the agenda due to environmental problems are considered. In this section, integrated reports of seven companies operating in the energy sector and publishing integrated reports are examined. Lastly, it proposes an integrated report template for the Turkish energy sector to contribute to future work.",signatures:"Gülçin Yıldırım, Tuğçe Uzun Kocamış and Figen Öker Türüdüoğlu",downloadPdfUrl:"/chapter/pdf-download/55449",previewPdfUrl:"/chapter/pdf-preview/55449",authors:[{id:"204492",title:"Prof.",name:"Figen",surname:"Öker Türüdüoğlu",slug:"figen-oker-turuduoglu",fullName:"Figen Öker Türüdüoğlu"},{id:"206372",title:"Dr.",name:"Tuğçe",surname:"Uzun Kocamiş",slug:"tugce-uzun-kocamis",fullName:"Tuğçe Uzun Kocamiş"},{id:"206373",title:"Mrs.",name:"Gülçin",surname:"Yildirim",slug:"gulcin-yildirim",fullName:"Gülçin Yildirim"}],corrections:null},{id:"54556",title:"Greening Accounting: An Inevitable Link to Help Firms Connect with Sustainability",doi:"10.5772/67936",slug:"greening-accounting-an-inevitable-link-to-help-firms-connect-with-sustainability",totalDownloads:1541,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The last decade has seen developments challenging the abilities of managerial accounting theories in supporting firms with environmental conscious decision-making that are grounded in the expanded accountability of firms toward nature and society. Critical theorists have argued that the shortcomings of the accounting theories to interpret the impacts of business activities on nature have its origin in the missing accounting standards, under-defined contractual boundaries, and the absence of a valid numéraire (monetary equivalency). In this chapter, the author posits that these shortcomings are a legacy of the economic paradigm within which the accounting frameworks operate and would remain so, unless a paradigm change evolves to handle environmental-related considerations on its own, even if it means rewriting rules to generate accounting interpretations of business activities. Instead of offering a methodological solution, this chapter ideates how having “environment” as integral to the accounting paradigm would enable firms in evaluating, accounting, and reporting environmental performance transparently and improve flow of information to help management face sustainability-related challenges better.",signatures:"Somnath Debnath",downloadPdfUrl:"/chapter/pdf-download/54556",previewPdfUrl:"/chapter/pdf-preview/54556",authors:[{id:"202694",title:"Dr.",name:"Somnath",surname:"Debnath",slug:"somnath-debnath",fullName:"Somnath Debnath"}],corrections:null},{id:"54829",title:"Greening Accounting II: Exploring Feasibility of Environmental Accounting Framework",doi:"10.5772/intechopen.68403",slug:"greening-accounting-ii-exploring-feasibility-of-environmental-accounting-framework",totalDownloads:1553,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Exploring the theme of greening accounting in the previous chapter led us to examine the challenges of managerial accounting in supporting firms with the environmentally conscious decision-making and ideate how integrating environmental viewpoint within accounting can be achieved through a new construct that would support firms in integrating ‘environmental well-being’ as a core concern. In this chapter, the argument is validated by experimenting with a real-life case study and exploring challenges to enact the proposed construct. This not only tests the feasibility of the construct from an accounting perspective, including how information generated through it could be leveraged to meet corresponding information needs of firms without sacrificing transparency and auditability, but also advances the argument of greening accounting to redefine how the concerned information needs of firms and stakeholders can be identified and perceived in relation to the micro-level application of sustainability.",signatures:"Somnath Debnath",downloadPdfUrl:"/chapter/pdf-download/54829",previewPdfUrl:"/chapter/pdf-preview/54829",authors:[{id:"202694",title:"Dr.",name:"Somnath",surname:"Debnath",slug:"somnath-debnath",fullName:"Somnath Debnath"}],corrections:null},{id:"55201",title:"Adaptation of International Accounting Standards: Case of Portugal",doi:"10.5772/intechopen.68732",slug:"adaptation-of-international-accounting-standards-case-of-portugal",totalDownloads:1661,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:1,abstract:"This chapter aims to present the results of a broad analysis about the process of accounting standardization in Portugal in order to frame the current situation and the different levels of standardization that characterize it. The methodology followed involves a broad revision of the literature and content analysis on various papers and texts as well on documents directly related with the study topic. It concludes with the identification and characterization of the current levels of accounting standardization and makes reference to the likely scenario of this regulatory framework in the short term. The objective is to understand how the evolution of accounting standards in Portugal has evolved, what the current situation is and its likely evolution in the near future. The chapter is also aimed at contributing to the understanding of the process of adaptation of international accounting standards to the Portuguese reality.",signatures:"Helena Isabel Barroso Saraiva, Maria‐Céu F.G. Alves and Vítor M.S.\nGabriel",downloadPdfUrl:"/chapter/pdf-download/55201",previewPdfUrl:"/chapter/pdf-preview/55201",authors:[{id:"108390",title:"Prof.",name:"Maria",surname:"do Céu Gaspar Alves",slug:"maria-do-ceu-gaspar-alves",fullName:"Maria do Céu Gaspar Alves"},{id:"203124",title:"Prof.",name:"Helena Isabel",surname:"B. Saraiva",slug:"helena-isabel-b.-saraiva",fullName:"Helena Isabel B. Saraiva"},{id:"203126",title:"Dr.",name:"Vítor",surname:"Gabriel",slug:"vitor-gabriel",fullName:"Vítor Gabriel"}],corrections:null},{id:"55268",title:"M2M-Fair Value Accounting",doi:"10.5772/intechopen.68724",slug:"m2m-fair-value-accounting",totalDownloads:3861,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"Since the past 20 years, the value relevance of financial information based on the historical cost method has been widely criticized among the academics and the preparers of financial information. The ongoing debate over the shortcomings of historical cost for ascertaining the worth of assets and liabilities and the rapid spread of fair value measurement for financial reporting has first led to the issuance of Financial Accounting Standard No. 157 Fair Value Measurements in September 2006 and then the initialization of fair value measurement project by the International Accounting Standards Board (IASB) and the Financial Accounting Standards Board in 2006 within the convergence project. On May 12, 2011, when the IASB issued IFRS 13 Fair Value Measurement, it appears that there has been substantial convergence between IFRS 13 and FASB 157. The purpose of this paper is to comprehensively explain the fair value accounting in accordance with IFRS 13 and describe the types of assets and liabilities that are subject to fair value accounting and their accompanying measurement principles with reference to other IFRSs and the Exposure Draft Conceptual Framework for Financial Reporting.",signatures:"Yıldız Özerhan and Banu Sultanoğlu",downloadPdfUrl:"/chapter/pdf-download/55268",previewPdfUrl:"/chapter/pdf-preview/55268",authors:[{id:"204283",title:"Dr.",name:"Banu",surname:"Sultanoglu",slug:"banu-sultanoglu",fullName:"Banu Sultanoglu"},{id:"204344",title:"Prof.",name:"Yildiz",surname:"Ozerhan",slug:"yildiz-ozerhan",fullName:"Yildiz Ozerhan"}],corrections:null},{id:"55448",title:"Reporting for Carbon Trading and International Accounting Standards",doi:"10.5772/intechopen.68959",slug:"reporting-for-carbon-trading-and-international-accounting-standards",totalDownloads:1772,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"During the first commitment period of the Kyoto Protocol, many developed countries were forced to restrict carbon emissions. Flexible mechanisms were initiated to reduce carbon emissions and support clean energy projects. Regulated carbon markets were established to trade carbon premiums produced by these projects by signatory countries, while carbon premiums produced by nonsignatory countries were traded in voluntary markets. Following limited participation in the Kyoto Protocol, by the leadership of European Union, 195 countries presented contributive ideas in Paris Agreement, which is the first-ever universal, legally binding global climate deal. Kyoto Protocol sets commitment targets that have legal force, while the Paris Agreement emphases on consensus building and allows for voluntary and nationally determined targets. Another key difference between Paris Agreement and the Kyoto Protocol is its scope. It does not provide a specific division between developed and developing nations. By means of these changes, trading in voluntary carbon markets is expected to increase due to the higher demand to offset unavoidable carbon emissions. There has been no authoritative guidance published on carbon accounting by the International Accounting Standards Board or the Financial Accounting Standards Board. This study proposes how to measure and report the carbon allowances and carbon credits.",signatures:"Figen Öker and Hümeyra Adıgüzel",downloadPdfUrl:"/chapter/pdf-download/55448",previewPdfUrl:"/chapter/pdf-preview/55448",authors:[{id:"204492",title:"Prof.",name:"Figen",surname:"Öker Türüdüoğlu",slug:"figen-oker-turuduoglu",fullName:"Figen Öker Türüdüoğlu"},{id:"204767",title:"Dr.",name:"Hümeyra",surname:"Adıgüzel",slug:"humeyra-adiguzel",fullName:"Hümeyra Adıgüzel"}],corrections:null},{id:"55626",title:"Accounting Choices in Corporate Financial Reporting: A Literature Review of Positive Accounting Theory",doi:"10.5772/intechopen.68962",slug:"accounting-choices-in-corporate-financial-reporting-a-literature-review-of-positive-accounting-theor",totalDownloads:5901,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:"This chapter aims to put light on the positive accounting theory and related empirical studies and identify its broad contributions to the accounting research. Our objective is to provide a review of positive accounting literature in order to synthesize findings, identify areas of controversy in the literature, and evaluate critiques. Positive research in accounting started coming to prominence around the mid-1960s and had been a vector of paradigm shift within the financial accounting research in the 1970s and 1980s. The positive accounting theory is developed by Watts and Zimmerman and is based on work undertaken in economics and is heavily dependent on the efficient market hypothesis, the capital assets pricing model, and agency theory. The three key hypotheses are bonus plan hypothesis, debt hypothesis, and political cost hypothesis. Nevertheless, PAT has been subjected to severe and numerous criticisms from different perspectives, which are critiques on research methods, its theoretical foundations, its logic on economics' basis, and its reference to philosophy of science. PAT and its hypotheses will continue to be a rich field of empirical research and the basic questions that it raises are still relevant today.",signatures:"İdil Kaya",downloadPdfUrl:"/chapter/pdf-download/55626",previewPdfUrl:"/chapter/pdf-preview/55626",authors:[{id:"204387",title:"Prof.",name:"Idil",surname:"Kaya",slug:"idil-kaya",fullName:"Idil Kaya"}],corrections:null},{id:"56092",title:"Value Relevance of Accounting Data in an Emerging Market: Did Accounting Reforms Make a Difference?",doi:"10.5772/intechopen.69103",slug:"value-relevance-of-accounting-data-in-an-emerging-market-did-accounting-reforms-make-a-difference-",totalDownloads:1462,totalCrossrefCites:3,totalDimensionsCites:3,hasAltmetrics:0,abstract:"This study investigates the association of accounting earnings (NI) and book value of equity (BV) with stock prices in Istanbul Stock Exchange (ISE), currently Borsa Istanbul (BIST), during the 1992–2006 period. We also explore the effect of accounting reforms on value relevance that is measured as the strength of the association between a firm’s NI and BV and its market value. We specifically investigate the impact of the Turkish Uniform Chart of Accounts (1994), mandatory inflation accounting, consolidations and voluntary (2003–2004), and the mandatory (2005) adoption of International Financial Reporting Standards (IFRS). We hypothesize that these reforms have reduced information asymmetry and thus are expected to enhance the value relevance of accounting information. We find strong evidence that the Ohlson model is a valid model, and BV is more value relevant than NI in BIST. We also find that inflation accounting and consolidations have enhanced the value relevance of BV, while IFRS has increased the value relevance of NI, but reduced that of BV. We contribute to the debate by exploiting the unique sequence of reforms, to come up with comparative value relevance testing designs and interesting results for all major reforms, which we believe will be instructive for researchers and for all emerging and developed economies undergoing similar reforms and best practices.",signatures:"Mine Aksu, Ayse Tansel Cetin and Can Simga Mugan",downloadPdfUrl:"/chapter/pdf-download/56092",previewPdfUrl:"/chapter/pdf-preview/56092",authors:[{id:"203574",title:"Associate Prof.",name:"Mine",surname:"Aksu",slug:"mine-aksu",fullName:"Mine Aksu"},{id:"204249",title:"Prof.",name:"Can Simga",surname:"Mugan",slug:"can-simga-mugan",fullName:"Can Simga Mugan"},{id:"204250",title:"Prof.",name:"Ayse",surname:"Tansel Cetin",slug:"ayse-tansel-cetin",fullName:"Ayse Tansel Cetin"}],corrections:null},{id:"55293",title:"Associativism of Accounting Professionals",doi:"10.5772/intechopen.68711",slug:"associativism-of-accounting-professionals",totalDownloads:1952,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"This chapter aims to discuss the role of professional accounting associations and orders in relation to the current context of accounting training. It is intended, with this, to broaden the discussion about the performance of these professional entities, since they are placed as of public interest. Its work with the universities, aiming to interfere in the training process of future professionals, whether by the application of evidence of access to the profession or by direct and indirect influence in the construction of the curricular contents intended to form the accountants, must be thought openly and free of ideological load. Thus, it is considered important to analyze the aspects of the relationship between universities and such class entities, in order to know if there is a disinterested relationship or if, on the contrary, the university is influenced by professional accounting associations and orders, in percussion of their selfish interests.",signatures:"Osmar Antonio Bonzanini, Amélia Cristina Ferreira da Silva and\nTeresa Gabriela Marques Leite",downloadPdfUrl:"/chapter/pdf-download/55293",previewPdfUrl:"/chapter/pdf-preview/55293",authors:[{id:"203815",title:"Dr.",name:"Osmar Antonio",surname:"Bonzanini",slug:"osmar-antonio-bonzanini",fullName:"Osmar Antonio Bonzanini"},{id:"204399",title:"Dr.",name:"Amélia Cristina",surname:"Ferreira Da Silva",slug:"amelia-cristina-ferreira-da-silva",fullName:"Amélia Cristina Ferreira Da Silva"},{id:"204400",title:"Dr.",name:"Teresa Gabriela",surname:"Marques Leite",slug:"teresa-gabriela-marques-leite",fullName:"Teresa Gabriela Marques Leite"}],corrections:null},{id:"55289",title:"Behavioral Accounting and its Interactions",doi:"10.5772/intechopen.68972",slug:"behavioral-accounting-and-its-interactions",totalDownloads:4046,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Behavioral accounting is a branch of accounting that is related to behavior besides the accounting knowledge. It deals with the attitude and behavior of people when they are encountered with an accounting phenomenon which determines the behavior that they will show in decision‐making. This special area of accounting addresses such aspects as human information‐processing behavior, judgment quality, accounting problems that are created by users and providers of accounting information, and accounting information users’ and producers’ decision‐making skills. Behavioral research tries to find out how individuals make decisions and interact and influence other individuals, organizations, markets, and society. Behavioral accounting concept is examined under the topics of the influence of accounting information on behavior, managerial control (budget participation, nonfinancial measures, leadership, and balanced scorecard), auditing (auditor‐client negotiations, auditor’s judgment, and decision‐making), and ethics (ethical decision‐making, ethical orientation, and rationalizations on unethical behavior) in this chapter.",signatures:"Filiz Angay Kutluk",downloadPdfUrl:"/chapter/pdf-download/55289",previewPdfUrl:"/chapter/pdf-preview/55289",authors:[{id:"203083",title:"Associate Prof.",name:"Filiz",surname:"Angay Kutluk",slug:"filiz-angay-kutluk",fullName:"Filiz Angay Kutluk"}],corrections:null},{id:"55533",title:"The Future of Accounting Profession in an Era of Start-Ups",doi:"10.5772/intechopen.69264",slug:"the-future-of-accounting-profession-in-an-era-of-start-ups",totalDownloads:2053,totalCrossrefCites:6,totalDimensionsCites:8,hasAltmetrics:0,abstract:"With the help of the advancements in the field of communication and information technologies, the number of IT-based software has rapidly increased and the capabilities of high-budget enterprise resource planning (ERP) software widely used by large enterprises have begun to be offered to small and medium-sized enterprises (SMEs). In this chapter, cloud computing and other information technologies based accounting start-ups are covered, and the effects of these highly increasing start-ups on the profession of accounting have been addressed. In conclusion, it has been predicted that technology-based accounting start-ups with both accounting professionals and entrepreneurs having an expertise on information technologies will come together and will increase in the future, and cloud-based accounting initiatives will shape the future of the profession.",signatures:"Burak Özdoğan",downloadPdfUrl:"/chapter/pdf-download/55533",previewPdfUrl:"/chapter/pdf-preview/55533",authors:[{id:"203445",title:"Dr.",name:"Burak",surname:"Ozdogan",slug:"burak-ozdogan",fullName:"Burak Ozdogan"}],corrections:null},{id:"54602",title:"Graphical and Textual Presentations in Financial Reports",doi:"10.5772/68038",slug:"graphical-and-textual-presentations-in-financial-reports",totalDownloads:1428,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The use of separate graphs and texts to disclose information is a frequent occurrence in corporate annual reports. Multiple sources of information does not enhance understanding of users of financial statements. This chapter compares spatially separated text and graphs with integrated presentations that aim at bringing text and graphs as close as possible to each other. The chapter begins by illustrating the concept of split attention. Cognitive load arises when disparate sources of accounting information need to be mentally integrated by users. An experiment using separate text and diagrams is then presented to demonstrate how participants can deal with cognitive overload when reading split-attention material. Using two instructional design formats, the split-attention format and the integrated format, first-year accounting students were used as surrogates for financial report user groups such as employees and shareholders. The presence of the split-attention effect in the financial accounting material was established. Effective use of text and diagrams in integrated reporting helps integrated thinking and assists the interconnectedness of information. The findings suggest that redesigning financial reports by integrating text and diagrams may make effective use of the available cognitive resources and possibly enhance investors and other stakeholders’ decision-making process.",signatures:"Seedwell T.M. Sithole",downloadPdfUrl:"/chapter/pdf-download/54602",previewPdfUrl:"/chapter/pdf-preview/54602",authors:[{id:"203186",title:"Dr.",name:"Seedwell T.M.",surname:"Sithole",slug:"seedwell-t.m.-sithole",fullName:"Seedwell T.M. Sithole"}],corrections:null},{id:"55587",title:"Historical Development of Government Accounting",doi:"10.5772/intechopen.69121",slug:"historical-development-of-government-accounting",totalDownloads:2795,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Government accounting aims at preventing waste in government services and establishing a balance between optimal expenditure and services by managing government assets and government sources in the most efficient way. This balance can be established only by obtaining complete and accurate information from government accounting system on time. Since the users have a low level of knowledge needs in government accounting system, it has been recorded for long years in a cash basis manner. However, as the government’s area of operation expanded and the needs increased, it became obvious that cash basis system had lacking parts. So it started to focus on recording financial transactions and financial reporting. These lacking parts in the accounting system tried to be overcome through a new regulation by focusing on the areas where cash basis accounting system was insufficient; and a change was experienced with regard to applying the accrual basis in the areas of government accounting and financial reporting. This study aims to explain the historical development of government accounting by applications in countries and especially by detailed expressions for Turkey. As a result of the literature review and the examination of countries’ government accounting practices, it has been determined that the government accounting practice has made the correct transition from cash basis to accrual basis.",signatures:"Mihriban Coşkun Arslan",downloadPdfUrl:"/chapter/pdf-download/55587",previewPdfUrl:"/chapter/pdf-preview/55587",authors:[{id:"203724",title:"Dr.",name:"Mihriban",surname:"Coşkun Arslan",slug:"mihriban-coskun-arslan",fullName:"Mihriban Coşkun Arslan"}],corrections:null},{id:"55385",title:"Public Accounting Reform from Institutional Theory Perspectives: Case of Turkey",doi:"10.5772/intechopen.68778",slug:"public-accounting-reform-from-institutional-theory-perspectives-case-of-turkey",totalDownloads:1723,totalCrossrefCites:1,totalDimensionsCites:3,hasAltmetrics:0,abstract:"In the literature, it is often found that institutional theory is used as the theoretical framework to explain the development and application of accounting. By means of these studies, it becomes easier to understand accounting as a social and political activity within itself and thus to be able to understand the economic, institutional, political and social environment of the turnover of the practices. In this regard, the main aim of this study is to explain the development of the public accounting system in Turkey with the help of institutional theory. Thus, it is aimed to explain all the dynamics that provide the institutionalization of state account in the national sense, together with the economic, political and social processes of the period in question. It is revealed that the regulatory arrangements directly contribute to the institutionalization of a field, and as a result, how the public organizations directly contribute to the institutionalization process.",signatures:"Ceray Aldemir and Tuğba Uçma Uysal",downloadPdfUrl:"/chapter/pdf-download/55385",previewPdfUrl:"/chapter/pdf-preview/55385",authors:[{id:"204342",title:"Dr.",name:"Ceray",surname:"Aldemir",slug:"ceray-aldemir",fullName:"Ceray Aldemir"},{id:"204348",title:"Dr.",name:"Tugba",surname:"Ucma Uysal",slug:"tugba-ucma-uysal",fullName:"Tugba Ucma Uysal"}],corrections:null},{id:"55750",title:"The Factors Used to Create Performance-Based Budgeting: A Research on Turkey",doi:"10.5772/intechopen.68920",slug:"the-factors-used-to-create-performance-based-budgeting-a-research-on-turkey",totalDownloads:1703,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Performance-based budgeting (PBB) is the practice of developing flexible financial management tools to increase the efficiency and productivity of public institutions both in developed and developing countries such as Turkey. It can be seen from international literature gathered as a result of researches that developing countries have come a long way in developing performance-based budgeting activities. In developed economies, successful international institutions such as Organization for Economic Cooperation and Development (OECD) and International Monetary Fund (IMF) promote the implementation of performance-based budgeting for a developing world. Fiscal transparency, medium-term expenditure framework, and other institutional arrangements are factors effective in developing performance-based budgeting. Budget experts regard these factors as important factors, and the view that it is difficult to implement these prevails. Within the context of this theory, the main purpose of this study is to determine the preparation and implementation of performance-based budgeting in public institutions of developing countries such as Turkey, which has an important economy in the world, and to measure the perception levels of employees working in these institutions. As a result of the confirmatory factor analysis (CFA) based on the main findings of the study, goodness-of-fit values of the measurement model were found to be sufficient. Independent t test and one-way ANOVA analyses were conducted to find out the perception levels of the participants in the study. As a result of the analyses, significant differences were found between demographic features and perception levels.",signatures:"Hakan Vahit Erkutlu, Şükran Güngör Tanç and Seyhan Çil Koçyiğit",downloadPdfUrl:"/chapter/pdf-download/55750",previewPdfUrl:"/chapter/pdf-preview/55750",authors:[{id:"204390",title:"Dr.",name:"Şükran",surname:"Güngör Tanç",slug:"sukran-gungor-tanc",fullName:"Şükran Güngör Tanç"},{id:"204391",title:"Prof.",name:"Hakan Vahit",surname:"Erkutlu",slug:"hakan-vahit-erkutlu",fullName:"Hakan Vahit Erkutlu"},{id:"204395",title:"Prof.",name:"Seyhan Çil",surname:"Koçyiğit",slug:"seyhan-cil-kocyigit",fullName:"Seyhan Çil Koçyiğit"}],corrections:null},{id:"54188",title:"The Managerial Perspective and Systems of Accountability in Judicial Offices",doi:"10.5772/67555",slug:"the-managerial-perspective-and-systems-of-accountability-in-judicial-offices",totalDownloads:1123,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In Italy, the machinery of justice has been, on more than one occasion, the subject of criticism. For the most part, the criticism has been relative to the slowness of trials and the inadequacy of the judicial system, deemed not capable of confronting the request for continuously evolving justice in an exhaustive manner, whose characteristics change in time based on the emerging needs of society. The analysis of the justice system was, in fact, generally not subject to enquiries on offices’ productivity and to evaluation of the management of resources invested in the sector. The same centres of data elaboration and the related departments at the Ministry of Justice, for example, have not gone much further than collecting the statistical data and creating the generic indicators of service quality. Such parameters, though, are often revealed to be too bureaucratic and of little use in proposing ameliorative solutions of the service offered to citizens, who desire levels of protection that are more responsive to their expectations. In this sense, the application of the system of accountability within the judicial system can contribute to the managerialization of the service.",signatures:"Ubaldo Comite",downloadPdfUrl:"/chapter/pdf-download/54188",previewPdfUrl:"/chapter/pdf-preview/54188",authors:[{id:"195399",title:"Prof.",name:"Ubaldo",surname:"Comite",slug:"ubaldo-comite",fullName:"Ubaldo Comite"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"6051",title:"Financial Management from an Emerging Market Perspective",subtitle:null,isOpenForSubmission:!1,hash:"48fd9d56d82da76c785db97e23ae398e",slug:"financial-management-from-an-emerging-market-perspective",bookSignature:"Guray Kucukkocaoglu and Soner Gokten",coverURL:"https://cdn.intechopen.com/books/images_new/6051.jpg",editedByType:"Edited by",editors:[{id:"70354",title:"Ph.D.",name:"Soner",surname:"Gokten",slug:"soner-gokten",fullName:"Soner Gokten"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6490",title:"Energy Management for Sustainable Development",subtitle:null,isOpenForSubmission:!1,hash:"a5e77ab7a4bfed7a2a1d524b8a3d6a90",slug:"energy-management-for-sustainable-development",bookSignature:"Soner Gokten and Guray Kucukkocaoglu",coverURL:"https://cdn.intechopen.com/books/images_new/6490.jpg",editedByType:"Edited by",editors:[{id:"70354",title:"Ph.D.",name:"Soner",surname:"Gokten",slug:"soner-gokten",fullName:"Soner Gokten"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6823",title:"Sustainability Assessment and Reporting",subtitle:null,isOpenForSubmission:!1,hash:"4db72204a34eff9b5143955463b293cf",slug:"sustainability-assessment-and-reporting",bookSignature:"Soner Gokten and Pinar Okan Gokten",coverURL:"https://cdn.intechopen.com/books/images_new/6823.jpg",editedByType:"Edited by",editors:[{id:"70354",title:"Ph.D.",name:"Soner",surname:"Gokten",slug:"soner-gokten",fullName:"Soner Gokten"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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\r\n\tCytokeratins are the most diverse and, arguably least understood components of the cytoskeleton. Comprising the intermediate filaments of epithelial cells, cytokeratins have roles in tissue integrity, in signaling, attachment to a substrate, and providing scaffolding to cytoplasmic organelles including, presumably, the nucleus. Essentially insoluble filamentous structures, these assemblies disappear during mitosis, to re-assemble immediately afterward. Beyond the confines of epithelial cells, keratins provide the bulk material to the epidermal stratum corneum, hair, nails and other rigid elements of the integument. Cytokeratins are obligate heteropolymers, consisting of equal amounts of Type I, acidic, and Type II neutral to basic proteins. In mammals, the Type I keratin genes are clustered in a single chromosomal region, and so are the Type II keratin genes. Different cytokeratins are characteristic molecular marker for specific epithelia, e.g., epidermis, cornea, tongue, hair etc. Mutations in keratin genes have dominant inheritance, in accordance with their obligate polymerization, and can cause severe disorders. Lately, first successes in correcting the mutant phenotype have been achieved using DNA-targeted therapies. Recent progress in studies of these fascinating proteins warrants a recap at this moment, which this volume aims to provide.
",isbn:null,printIsbn:"979-953-307-X-X",pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"5b6f7c428ae46faa9e16125459bedbff",bookSignature:"Dr. Miroslav Blumenberg",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/9775.jpg",keywords:"Cytoplasm, Cytokeratin-associated Proteins, Signal Transduction, Actin, Tubulin, Integrins, Extracellular Matrix, Disruptions and Diseases, Promoters, Transcription Factors, Tissue Specificity, Keratinopathies",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 8th 2020",dateEndSecondStepPublish:"October 6th 2020",dateEndThirdStepPublish:"December 5th 2020",dateEndFourthStepPublish:"February 23rd 2021",dateEndFifthStepPublish:"April 24th 2021",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"2 years",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"Dr. Blumenberg pioneered the use of DNA microarrays in skin biology. His H-index of 35 is a clear indicator of his merit and impact as a researcher. He serves on editorial boards of BMC Genomics, Acta Dermatovenerologica APA, and World Journal of Biological Chemistry and holds three patents.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. 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However, identifying face images across widespread range of ages is shortcoming due to human face appearance changes affected by aging process [6, 7]. In order to achieve human face recognition under difference ages, Age-Invariant Face Recognition (AIFR) approach is progressed [8]. AIFR recognizes faces using facial features extracted from human images. AIFR method uses three different models such as generative, discriminative [9], and deep learning methods [10]. Generative approaches are based on the age progression methods in regard to converting the probe image into the same age as that of gallery image [11]. However, generative schemes have several shortcomings [12]. Optimizing the recognition performance in generative model is not easier task. Estimating the accurate results in generative model is highly difficult since it cannot handle aging impact. Discriminative approaches [13] are introduced to resolve discrepancy of generative scheme [14]. It develops feature matching using local descriptors [15] in AIFR. Multiple descriptors-based AIFR is introduced to extract features from periocular region [16]. In this, two descriptors are used to extract features that are Scale-Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF).
In order to achieve better result in AIFR, deep learning method is integrated with discriminative approach [17]. In deep learning, Convolutional Neural Network (CNN) algorithm plays vital role in recognizing face with different aging images [18]. Large age gap verification is performed by injecting features in deep networks [19]. Here, deep CNN is used to recognize face where texture features are considered. Aging model-based face recognition with different aging images is introduced under deep learning method [20]. Here, CNN descriptor is utilized to match image with different aging images.
From the aforesaid studies, we determine that there are still many issues present in recognizing face with aging progress. The issues are discussed as follows:
Preprocessing is not effective in most of the chapter that reduces performance of the system.
Pose normalization is not considered in existing AIFR, which is highly significant. Since, AIFR datasets such as MORPH, FG-NET, etc., contain different pose images.
Existing feature extraction procedures lack in extracting features from important regions that tend to reduce recognition rate.
Face recognition algorithms are not up to the level to handle large dataset and thus reduce the result of accuracy.
These problems impose confines on the present AIFR systems and also complicate the recognition and retrieval task especially under different aging images.
In order to tackle abovementioned issues, our work contributes the following processes:
In order to reduce time wastages in preprocessing, we initially execute novel Image Quality Evaluation (IQE) method, which estimates Image Quality Metric (IQM) for each image. If IQM value is below Image Quality Threshold (IQT), then only preprocessing is performed for that image or else directly gone into the pose normalization process.
Preprocessing is performed to reduce uncertainties in upcoming face recognition processes such as feature extraction, recognition, and retrieval. For this purpose, we implement two processes such as illumination normalization and noise removal. Illumination normalization adopts DGC-CLAHE and noise removal adopts ASBF algorithm.
Pose normalization is significant to diminish difficulties present in feature extraction and thus enhances the recognition and retrieval performance.
Our work extracts feature from three regions that are periocular, nose, and mouth in order to increase recognition rate. Here, two descriptors are utilized that are CNN and SIHKS, which perform better than other existing descriptors such as LBP, SIFT, etc.
In order to reduce recognition and retrieval time, we fuse features after extraction using CCA.
Recognition and retrieval are performed through SVM algorithm, which performs well even with unstructured, semistructured data such as text, images, and trees.
Outline of this chapter is summarized as follows: Section 2 deliberates state-of-the-art works existing in AIFR with their limitations. Section 3 exemplifies problems occurring in previous works related to AIFR. Section 4 explains brief study of our proposed work with our proposed algorithms. Section 5 illustrates numerical results obtain from our simulation environment and also compares it with existing methods. Finally, section 6 concludes our contribution and also provides comment on our future work.
This section discusses the state-of-the-art work related to AIFR along with their limitations. In this, we discussed works that comprise preprocessing, feature extraction, recognition, and retrieval processes.
Kishore et al. [21] have suggested Periocular Region-Based AIFR Using Local Binary Pattern. In this, three sequential processes are executed to recognize faces that are preprocessing, feature extraction, and classification. In preprocessing, enhancement and denoising processes are employed in each facial image. Local Binary Pattern (LBP) descriptor [22] was used to extract features from the periocular region [23] of the given face image. Periocular region contains eyes, eye lashes, and eye brow parts of the face. Chi-square distance was used as classifier to recognize face after feature extraction. Chi-square distance doesn’t recognize face accurately since it is highly sensitive to the sample size.
Nanni et al. [24] have introduced ensemble of texture descriptor and preprocessing techniques to recognize image effectually. Four face recognition processes are performed that are preprocessing, feature extraction, feature transform, and classification. Preprocessing executes three techniques that are adaptive single index retinex (AR) in order to enhance scene detail and color enhancement in darker area. Anisotropic smoothing and different of Gaussian (DoG) are algorithms executed to normalize the illumination field. Features are extracted using two descriptors that are Patterns of the Oriented Edge Magnitudes (POEM) and the Monogenic Binary Coding (MBC). At last, different distance functions are used to recognize face. Accuracy of face recognition was very less due to poor feature extraction mechanism. Chi et al. [25] have offered temporal nonvolume preserving approach to facial age progression and AIFR. In preprocessing, face region was detected and aligned based on the fixed position of the eyes and mouth corners. And then it maps the texture features of the test image with the trained image in order to verify images. Here, deep CNN algorithm was utilized to map features. In this, preprocessing step doesn’t perform effective processes such as normalization, noise removal that tend to reduce system performance.
Bor et al. [26] have introduced Cross Age Reference Coding (CARC) for AIFR. Initially, it executes face detection algorithm in order to detect face region in image. And it extracts features from the detected region for which it utilizes high-dimensional LBP algorithm. LBP extracts 59 local features from the detection regions. In this, Principal Component Analysis (PCA) algorithm was used to reduce dimensionality of extracted feature. After that, CARC recognizes face using local features transformation. More analysis is required on feature extraction since it plays vital role in AIFR. Yali et al. [27] have pointed out distance metric optimization driven CNN for AIFR. Here, two models are integrated that are feature learning and distance metric learning. This integration is achieved through CNN algorithm with parameters optimized using network propagation algorithm. CNN learns features using the convolution layer and recognizes face using the distance metric. Finally, recognized images are retrieved effectually. Herein, recognition rate was very less due to ineffective feature extraction.
Pournami et al. [28] have offered deep learning and multiclass SVM algorithm to recognize face. Here, preprocessing was performed to increase the accuracy of the face recognition where image resizing was performed. CNN feature descriptor was used to extract features from the given image. Here, fully connected layer extracts features from the image and then features are given as input to the multiclass SVM classifier. Resizing only performed in preprocessing thus introduced more noise in extracted feature. Garima et al. [29] have suggested techniques for face verification across different age progression with large age gap. Initially, image normalization was performed where RGB image was converted into the grayscale image and the image is rotate as the eyes are aligned horizontally. In this, face features are extracted using Center Symmetric Local binary Pattern (CSLBP) algorithm. And also weighted K-nearest Neighbor (K-NN) algorithm was used to recognize face from extracted features. K-NN doesn’t perform well for large dataset and thus reduces the accuracy of face recognition. Saroj et al. [30] have pointed out pyramid binary pattern for age-invariant face verification. In this, pyramid binary pattern was used to extract texture feature. Texture features are given as input to the PCA in order to reduce dimensionality of the extracted features. And then, classification was performed through SVM algorithm. Here, texture feature was only extracted to classify the face with age invariant. Thus it reduces accuracy in face recognition since dataset contains different images with large age gap.
Mrudula et al. [31] have offered face recognition across aging using GLBP features. Preprocessing performs three sequential processes that are image resizing, RGB to gray, and illumination normalization. Here, combined feature descriptor was used to extract features from the given image. LBP and Gabor descriptors are combined, which was known as GLBP descriptor. During classification, PCA was used to reduce feature dimensionality and K-NN algorithm was used to recognize face across aging. Herein, GLBP descriptor introduces high false-positive rate in age-invariant face recognition. Zhen et al. [32] have pointed out local polynomial contrast binary patterns for face recognition. Polynomial filters are used to extract the attributes from the given image. In this, LBP descriptor was used to extract texture from the given image. Fisher Linear Discriminant (FLD) algorithm is used to reduce dimension of extracted features. Here, extracted features are classified using nearest neighbor classifier to recognize given image in training set. Nearest neighbor classifier consumes more time to classify image since all the work is performed in testing stages only.
Mohanraj et al. [33] have suggested ensemble of CNN for face recognition in order to resolve aging, pose variation, and low-resolution problem. Preprocessing was established to resize the given image. After that, features are extracted using three different CNN algorithms. Features are concatenated and given to the classifier in order to predict the person. Here, random forest classifier is used to recognize the face. Noise removal was not performed in preprocessing and thus reduces the accuracy of face recognition. Rupali et al. [34] have introduced component-based face recognition. Here, three face components are considered that are nose, lips, and ears. Preprocessing is performed to resize the image and features are extracted using CNN algorithm. Features are extracted from nose and face regions that are given to the FLD algorithm to reduce the dimensions. These features are given to KNN classifier in order to predict the image. In KNN, initial K value prediction is complex that leads to ineffective results. Venkata et al. [35] have pointed out real-time face recognition using deep learning and LBP. During preprocessing, it resizes the given image. In this, LBP was used to extract features from the given images. Extracted features are given to the CNN in order to provide weight to each feature. CNN provides weight in order to estimate the matched face with the training images. Here, texture feature only extracted to recognize face across aging that tends to reduce recognition rate.
Mohsen et al. [36] have offered age-based human face image retrieval using zernike moments. In this, Zernike moment was used to extract features from the images. Here, Zernike moment utilizes Zernike Basis Function (ZBF), which captures both local and global featured fro face image. And, Multi-Layer Perceptron (MLP) algorithm was used to recognize age in training image. Accurate result was not obtained in MLP classifier, thus reducing the recognition rate. Danbei et al. [37] have offered face aging synthesis application based on feature fusion. Initially, face detection was performed and feature points are positioned. For this purpose, triangulation and affine transformations are used, which position the feature points. Here, facial texture features are extracted to recognize face across aging. Extracted features are fused in order to recognize face with the training images effectually. More analysis is required on facial recognition since it describes up to feature fusion process.
Kishore et al. [38] have offered Hybrid Local Descriptor (HLD) and LDA-assisted K-Nearest Neighbor classification in AIFR. Here, Gaussian filter was used to reduce noise that results in information degradation, since it removes fine details of the image and resultant image is blurred. WLD-based feature extraction loses more information due to lack of pixel consideration. K-NN-based classification requires more time due to absence of training phase and finding good similarity measure is also difficult. Muhammad et al. [39] have introduced Demographic Features (DF)-assisted AIFR and retrieval. In this, feature extraction takes more time, since each feature was extracted in three individual CNNs. Position and orientation of the object were ignored in hidden layer of CNN that result in less accuracy in feature extraction and recognition. Chenfei et al. [40] have pointed out Coupled Auto Encoder (CAN) algorithm based feature extraction in AIFR. Herein, feature extraction was not effective due to lack of texture and shape-oriented features. In CAN, data relationships are not considered that affect classification results and weight computation is also very difficult. Huiling et al. [41] have introduced Identity Inference Model (IIM)-based age subspace learning to recognize image in AIFR. Herein, wLBP-based feature extraction was used that results in less accuracy, since it contains more noise in extracted features due to absence of noise removal process. Fahad et al. [42] have introduced Composite Temporal Spatio (CTS) modeling in order to recognize image in AIFR. Here, preprocessing was required to improve the accuracy in age-invariant face recognition, since image database contains illumination, pose variation, etc. Naïve Bayes–based classification results are always biased one, since it doesn’t rely on class conditional dependency.
This section briefly describes our proposed method in detail along with the description of utilized algorithm.
Our Multi-Feature-assisted AIFR (MF-AIFR) method tackles problems that are present in the previous AIFR works. For this purpose, MF-AIFR establishes the five consecutive processes that are IQE, Preprocessing, Pose Normalization, Feature Extraction and Fusion, Feature Recognition and Retrieval as depicted in Figure 1. Our work novelty is present in the IQE method, since previous AIFR method doesn’t concentrate on the quality evaluation. In order to save time, MF-AIFR performs IQE where images that are not satisfied IQT only given to the preprocessing step or else it is directly given to the pose normalization process. During preprocessing, MF-AIFR performs two processes that are illumination normalization using DGC-CLAHE and noise removal using ASBF algorithm. Pose normalization is executed to enhance feature extraction performance where EA-AT algorithm is utilized. Multiple features are extracted from the three different regions of face image that are periocular, mouth, and nose in regard to enhancing accuracy result. Here, two descriptors are executed that are CNN for texture feature and SIHKS for demographic and shape features extraction. Here, demographic features comprise age, gender, and race. Extracted features are fused using CCA in accord to reduce the complex recognition process. For recognition and retrieval, MF-AIFR pursues SVM algorithm, which has high scalability compared with other machine learning algorithm.
Architecture for proposed work.
Figure 1 illustrates the architecture for our proposed work. The process depicted in architecture is described briefly in upcoming sections.
Reducing computation time in AIFR and retrieval is noteworthy in order to achieve efficient performance. For this purpose, MF-AIFR performs novel IQE, which estimates IQM for each image. IQM comprises subsequent metrics that are Brightness
These metrics are designated as follows:
Where
Where
Where
Where
Where
Where
Using above parameters, we estimate IQM for each image. It can be measured as follows:
After computing IQM, this value is compared with the IQT in order to select whether next process is preprocessing or pose normalization for given image.
Where
MF-AIFR performs preprocessing in order to enhance the recognition rate in simulation results. For this purpose, we perform two processes in preprocessing that are illumination normalization and Noise removal.
Illumination normalization is performed in order to enhance the image quality and also avoid negative effects of the image. MF-AIFR adopts DGC-CLAHE algorithm for illumination normalization. Proposed DGC-CLAHE performs better than existing CLAHE method. It enhances both luminance and contrast of the image adaptively. Our DGC-CLAHE algorithm performs dual gamma correction, which enhances the dark areas of the image. This algorithm adaptively sets the clip points of each image, which depends on the dynamic range of each block of the image. In this, first gamma correction is executed to boost the entire luminance present in the image block. Second gamma correction is executed to adjust the contrast in very dark region in order to avoid overenhancement in bright regions.
Initially, DGC-CLAHE sets clip point adaptively based on the dynamic range, which can be expressed as follows:
Where
DGC-CLAHE defines enhancement weight for the global gray levels of the blocks by first gamma correction (
Where
Where
Noise removal is substantial process in face recognition in regard to enhancing recognition accuracy. For this purpose, our MF-AIFR utilizes ASBF algorithm to remove noise from given image. Proposed ASBF algorithm preserves fine details of the image while removing noise and also sharpens the image. ASBF algorithm is used to remove universal noises such as impulse and Gaussian.
In ASBF algorithm, noisy pixel is detected using Sorted Quadrant Median Vector (SQMV), which incorporates significant features such as edge or texture information. Our ASBF algorithm executes three sequential processes as depicted in Figure 2. Initially, Adaptive Median Filter (AMF) is used to identify the corrupted pixels in the image. Secondly, the edge of the image is preserved using edge detector, which accurately predicts the edge existence in the current window. Noise detector is used to classify the noise into impulse and Gaussian. Switching Bilateral Filter (SBF) contains ranging filter, which switches the modes between impulse and Gaussian based on noise detector result.
ASBF function blocks.
Existing noise filtering algorithm utilizes constant window size such as 3*3, which may fail to distinguish noisy and noise-free pixel accurately and thus results in blur output image. In order to avoid this drawback, our AMF adaptively changes the window size based on the number of noisy pixels present in given image.
Noise detector is used to predict whether pixel is filtered by SBF Gaussian (
At last, pixel with Gaussian and impulse noises are classified based on the above discussed conditions. These outputs are given as input to the SBF with SQMV.
The output from the SBF filter is expressed as follows:
Where
From the above discussions, we conclude that our proposed ASBF removes not only Gaussian noise but also impulse noise while keeping the image fine details and images. This way of performing preprocessing increases the accuracy in AIFR.
Pose normalization is substantial process to increase accuracy in face recognition. Since, our database FG-NET contains different pose images and thus requires pose normalization before entering into feature extraction and retrieval. Our MF-AIFR carried out EA-AT algorithm in order to correct the different poses into the frontal view and thus increases the feature extraction efficiency. EA-AT algorithm initially estimates pose angle of given image using Euler Angle. Then, estimated angle is provided to the Affine Transformation to get frontal view of the given image. Euler angles are three angles in order to describe the orientation of the face with respect to the fixed coordinate.
Figure 3 illustrates the Euler angle with their coordinates in Z vector. Three angles are describes as follows: Yaw, Pitch, and Roll. In this, yaw angle (
Euler angles representation.
Where
Roll angle (
Pitch angle (
These three angles are given as input to the affine transformation algorithm in order to rotate into the correct view. There exist four basic affine transformations that are illustrated as follows:
Translate—It moves a set of point in fixed distance in x and y.
Scale—It scales the set of points in up or down directions.
Rotate—It rotates the set of points about the origin.
Shear—It offsets a set of points in distance proportional to their x and y coordinates.
In mathematical form, an affine transformation of
Where,
Where
Feature extraction and fusion are a major part of this work in order to produce optimum results in AIFR. Our MF-AIFR extracts multiple features from three set of regions. We extract images from three regions that are periocular, nose, and mouth. Since, these three regions are significant to recognize the image across aging. From these regions, we extract three type of features that are texture, shape, and demographic, which are briefed in Table 1. Here, texture feature is extracted using the CNN descriptor, and SIHKS descriptor is used to extract the shape and demographic-related features.
Features | Feature description | Types of features |
---|---|---|
Texture | Texture feature represents the surface characteristics of the image | Contrast, Dissimilarity, Entropy, Homogeneity, Correlation, and Angular Second Moment |
Shape | Shape features represents the physiological identity of given image | Boundary of the periocular, nose, and mouth regions, Convexity, and Solidity |
Demographic | Demographic features represent the individual uniqueness of the given image. | Race, Age, and gender |
Features description.
Our MF-AIFR utilizes CNN descriptor for texture feature extraction since it provides robust performance in learning features layer by layer. CNN applies multiple filters on the raw input image in order to extract high-level features. Here, we extract six texture features in given image such as contrast, dissimilarity, entropy, homogeneity, correlation, and angular second moment. These features are described as follows: In CNN, three different types of layers are present that are Convolutional layer, Polling layer, and Fully connected layer.
It gathers image from the input layer, which is made up of a set of learnable filters. In our work, convolutional layer comprises six filters in order to generate feature map. Six filters in the convolutional layer generate six feature maps. The feature map is the consequence of the every filter that convolved through whole image. Convolution operation can be described as follows:
Where
It is used to perform downsampling operation in order to reduce the spatial size of the convolutional layers. Polling operation is implemented on the pixel values captured by the pooling mask. The pooling operation is described as follows:
Where
Fully connected layer is used to extract the features that are obtained in the preceding layers. The results obtained in the last convolutional and pooling layer are given as input to the fully connected layer in order extract features.
Shape and demographic features are extracted using SIHKS algorithm. Shape features are boundary of the eye, nose and mouth, Convexity, and Solidity. Demographic features comprise age, race, and gender information. Here, race feature represents the skin tone of the face image. These features plays key role in recognizing face across aging.
Proposed SIHKS descriptor performs better than HKS algorithm since conventional method has drawback such as sensitivity to scale especially to the global scale. Hence, we proposed SIHKS algorithm, which performs better in scale invariance, and it is able perform at any point even at scale selection is impossible. In addition to it, it also performs well extracting shape and demographic-oriented features compared with other shape feature descriptor. SIHKS extracts features using three steps that are listed as follows:
Logarithmical sampling in time t. It can be expressed using below equation.
Where
Taking logarithm of heat signature with time variations. It can be described as the below equation,
Where
Taking discrete time Fourier transform of heat signature. It can be expressed as below equation,
With the above steps, our SIKHS estimates scale-invariant quantity
Figure 4 illustrates the texture feature extraction in CNN with their significant layers such as convolutional layer, pool layer, and fully connected layer.
Feature extraction in CNN.
Feature fusion is estimated to reduce extracted feature dimension of extracted features such as shape, texture, and demographic features. This dimensionality reduction will result in better performance in face recognition, which the process of recognition and retrieval is easier. For this purpose, our MF-AIFR algorithm utilizes CCA algorithm, which performs effectively in feature fusion. Feature fusion is defined as the combination of multiple feature vectors into single feature vector. Proposed CCA is a statistical tool for recognizing linear relationship among sets of features vectors in order to determine the inter subject covariances. Canonical covariates of the given feature vectors are obtained using below expression,
Where
Recognition and retrieval are final process in our MF-AIFR, which is performed by utilizing SVM algorithm. Here, we select SVM algorithm to correctly recognize the face cross aging and also retrieve the recognized image for given input image. Figure 5 illustrates the input and output space models of the SVM algorithm.
SVM input and feature space representation.
Proposed SVM algorithm performs well in even unstructured and semistructured data. It addition to it, SVM also scales relatively well to high dimensionality of database. SVM gets input as fused features from previous process obtained using CCA algorithm. SVM is the binary classification method that discovers the optimal linear decision surface based on the concept of structural risk minimization. The decision surface represents the weighted combination of the elements present in the training set. These elements are illustrated as the support vectors and characterize the boundary between two different classes. The output of the SVM algorithm is a set of support vectors
The linear surface is represented as follows:
Where k represents the weight factor and b represents the bias term and z represents the training or testing data. These two parameters are used separate the hyperplane position and orientation. The weight factor k is calculated using below expression,
Kernel function plays vital role in SVM, which classifies features effectually. In MF-AIFR, we use Radial Basis Function (RBF) kernel. RBF performs well compared with other kernel functions. It doesn’t require any prior knowledge about data. It can be expressed as follows:
Here,
To characterize the performance of the proposed MF-AIFR, this section is divided into four aspects such as dataset description, simulation setup, application scenario, results, and discussion.
This section deliberates dataset information used in this chapter. Here, we utilize FG-NET database to perform face recognition and retrieval. Face and gesture recognition NETwork (FG-NET) aging database was released in the year of 2004 in an attempt to support research activities regarding the changes in the facial appearance caused by aging. FG-NET database comprises 1002 images from 82 different subjects. Each subject comprises 6–18 images with the age ranging between the newborns to the 69-year-old subjects. Our FG-NET database contains considerable variations such as poses and illuminations.
Table 2 illustrates the details of the FG-NET dataset briefly. Dataset contains 34 male subjects and 48 female subjects’ images. Each subject has 1–12 images across their age progression.
Parameters | Values | # Images |
---|---|---|
# subjects | 82 | 1002 |
#Males | 34 | Max (1–12) per subject |
#Females | 48 | Max (1–12) per subject |
Dataset description.
Different age bands present in the FG-NET dataset are represented in Table 3. FG-NET dataset comprises subjects from the age of 0 to 69 years old.
Factors | Ages | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
0–5 | 6–10 | 11–15 | 16–20 | 21–25 | 26–30 | 31–35 | 36–40 | 41–45 | 46–69 | |
#Subjects | 75 | 70 | 71 | 68 | 46 | 38 | 30 | 24 | 19 | 10 |
#Images | 233 | 178 | 164 | 155 | 81 | 62 | 38 | 31 | 26 | 34 |
Different age bands of FG-NET dataset.
Our proposed MF-AIFR is implemented in MATLAB R2017b tool with C programming language. Our MATLABR2017b is executed in windows operating system. MATLAB is a multi-paradigm statistical computing environment developed by MathWorks. MATLAB permits matrix manipulations, implementation of algorithms plotting of functions and data, creation of user interfaces, and interfacing with programs written in other languages, which include C, C++, C#, JAVA, and Python.
To evaluate performance of the MF-AIFR, we consider following metrics that are described as follows:
Where
Where
This compares the simulation results of the MF-AIFR with existing methods such as HLD, DF, and CAN. Here, we compare results using six performance metrics that are Accuracy, Recall, Precision, Recognition Rate, Rank-1 Score, and F-Score. Table 4 illustrates the comparisons of previous methods with their strength, weakness, and research statements.
Accuracy metric is one of the significant metrics to evaluate the performance of the proposed work. This metric defines the how accurate our MF-AIFR in terms of correct classification of images. The performance of this metric is evaluated by alternating the number of images.
Figure 6 demonstrates that comparisons on accuracy of the MF-AIFR with respect to the existing methods such as CAN, DF, and HLD. These comparisons show that our MF-AIFR achieves better performance compared with the existing methods. Since, our method utilizes better feature descriptors such as CNN and SIHKS. Both algorithms extract features effectually from three regions that are periocular, nose, and mouth. This selected region plays a key role in recognizing face across aging. And CNN and SIHKS provide robust performance even in high-dimensional dataset. As a result, our method achieves high accuracy as 95%. By contrast, CAN and DF method attain less accuracy compared with our method due to its poor feature extraction procedures since it doesn’t concentrate on the vital regions such as periocular, nose, and mouth. Meanwhile, HLD obtains high accuracy compared with both CAN and DF method due to its feature extraction from periocular region, which plays significant role in face recognition across aging. Though, it achieves less accuracy compared with our method due to its poor descriptor algorithm since it loses large amount of information during feature extraction.
Comparisons on accuracy.
Table 5 illustrates the average simulation results comparison of accuracy with the existing and proposed methods.
Reference | Key concentration | Strength | Weakness | Research statements | |||||
---|---|---|---|---|---|---|---|---|---|
Accuracy | Recall | Precision | Recognition rate | F-Score | Rank 1-score | ||||
Kishore et al. [41] | HLD-AIFR & Retrieval | Adopts large datasets | It removes fine details of the image and resultant image is blurred. Feature extraction loses more information due to lack of pixel consideration. | Low | Medium | Low | Low | Medium | Low |
Muhammad et al. [42] | DF-AIFR & Retrieval | Better demographic Estimation | Takes more time in feature extraction | Very Low | Low | Low | Very Low | Low | Very Low |
Chenfei et al. [13] | CAN-AIFR | Complexity is less | Data relationships are not considered that affects the recognition results. | Low | Medium | Very Low | Low | Low | Low |
Huiling et al. [15] | IIM-AIFR | Flexible to large dataset | More noise in extracted features due to absence of noise removal | Medium | Low | Very Low | Medium | Very Low | Low |
Fahad et al. [9] | CTS-AIFR | Recognition time is less | Naïve Bayes based recognition results are always biased one, since it doesn’t rely on class conditional dependency. | Very Low | Medium | Very Low | Very Low | Very Low | Low |
Comparisons on previous methods in AIFR.
Methods | Accuracy (%) |
---|---|
HLD | 80.2 |
DF | 73.2 |
CAN | 67.6 |
MF-AIFR | 90.2 |
Accuracy comparisons [average].
From the above comparison, it is noticed that our method achieves better accuracy percentage as 90.2% compared with the existing methods.
Recall is used to evaluate the performance of the MF-AIFR in terms of the correct recognition of face image. Recall performance is evaluated by changing the number of images.
Figure 7 shows that our MF-AIFR achieves less recall percentage compared with other methods.
Comparisons on recall.
Since, our MF-AIFR correctly recognizes the face as per given test image, thus reduces false detection of face images. Reason for this is that our method executes pose normalization before entering into the feature extraction process. Pose normalization enhances the feature extraction efficiency. Thus it leads to correct identification and retrieval of the test image. As a result, our MF-AIFR achieves less recall percentages compared with existing methods. Whereas existing methods such as DF and CAN achieves high recall percentages due to lack of pose normalization and complex feature extraction procedures. In the meantime, HLD method reduces recall percentage compared with DF and CAN methods since it doesn’t follow complex feature extraction procedures. Still, recall of HLD is high compared with MF-AIFR due to lack of pose normalization and information degradation in noise removal process. Table 6 designates the average simulation results comparison of recall with the existing and proposed methods.
Methods | Recall (%) |
---|---|
HLD | 75.6 |
DF | 87 |
CAN | 80 |
MF-AIFR | 70 |
Recall comparisons [average].
From the above comparison results, it is seen that our MF-AIFR method achieves less recall percentage as 70% compared with the existing methods.
Precision is used to measure performance of our work in terms of relevance instances retrieved compared with the total images. Precision performance is measured via altering the number of image.
Figure 8 depicts that MF-AIFR achieves high precision percentages compared with existing methods. MF-AIFR performs preprocessing process before entering into the feature extraction and recognition process. Preprocessing performs illumination normalization and noise filtering since our FG-NET dataset contains illumination and noises in images. These two processes enhance the quality of the image that tends to easy the feature extraction and recognition process. CAN and DF methods achieves less precision due to lack of preprocessing such as noise removal and illumination normalization. Likewise, HLD also obtains less precision owing to fine detail removal in Gaussian-based noise filtering. Since Gaussian filter doesn’t concentrate on fine details of the image, which results in blur image.
Comparisons on precision.
Table 7 designates the average simulation results comparison of precision with the existing and proposed methods. From the above comparison, we conclude that MF-AIFR achieves better precision percentage as 90.6% compared with existing methods.
Methods | Precision (%) |
---|---|
HLD | 81.6 |
DF | 71.6 |
CAN | 65 |
MF-AIFR | 90.6 |
Precision comparisons [average].
F-Score metric considers both false positive and false negative values in account to estimate performance of this work. The performance of this metric is simulated by varying the number of images.
Figure 9 illustrates that comparison on F-Score result of MF-AIFR with existing methods such as DF, CAN, and HLD. From this figure, it is noticed that our method achieves high F-Score compared with existing methods. Our MF-AIFR uses two descriptors such as CNN and SIHKS to extract texture, shape, and demographic features. Here, SIHKS descriptor performs very well in scale invariance and also provides better extraction results even when scale selection is impossible. It extracts shape and demographic features effectually, which plays substantial role in face recognition across aging. At the same time, CAN and DF methods attain less F-Score owing to the absence of significant feature extraction such as texture and shape features. Meanwhile, HLD also attains less F-Score since it doesn’t concentrate on shape features extraction and thus reduces the face recognition and retrieval efficiency.
Comparisons on F-score.
Table 8 describes the average simulation results comparison of F-Score with the existing and proposed methods. From the above comparison, we observed that MF-AIFR method achieves high F-Score percentage as 87.2% compared with existing methods.
Methods | F-Score (%) |
---|---|
HLD | 78.6 |
DF | 71.6 |
CAN | 59.6 |
MF-AIFR | 87.2 |
F-score comparisons [average].
Recognition rate is used to measure the ability of MF-AIFR in terms of the face recognition. It can be measured through changing the number of features.
Figure 10 designates the comparisons on recognition rate of MF-AIFR with respect to the existing methods CAN, DF, and HLD methods. From this figure, it is observed that our MF-AIFR attains high recognition rate compared with existing method. We propose SVM algorithm for recognition and retrieval. It performs well in recognition even in high dimensionality of dataset. In addition to it, we also perform feature fusion before entering into the recognition and retrieval process.
Comparisons on recognition rate.
Feature fusion reduces the dimension of feature vectors and thus tends to enhance the performance of SVM algorithm. Therefore, our method achieves better recognition rate compared with existing method. Meanwhile, DF method has less recognition rate compared with other methods due to lack of effective recognition and retrieval processes since it simply ranks the images. Likewise, CAN also attains less recognition rate compared with our method since it isn’t able to establish data relationship between different features. Meantime, HLD method attains less recognition rate due to usage of KNN for recognition. KNN takes more time, and discovering similarity measure is tedious.
Table 9 defines the average simulation results comparison of recognition rate with the existing and proposed methods. Above comparison illustrates that recognition rate of MF-AIFR is higher than that of other existing methods.
Methods | Recognition rate (%) |
---|---|
HLD | 87 |
DF | 69.2 |
CAN | 79.2 |
MF-AIFR | 92.2 |
Recognition rate comparisons [average].
Rank-1 Score considers the performance of cumulative match for given images in proposed work. It represents the efficacy of our work in terms of recognition and retrieval.
Figure 11 exhibits comparisons on rank-1 score results with respect to the existing methods. From this figure, it is seen that our MF-AIFR attains high rank-1 score compared with the existing methods. Our proposed DGC-CLAHE algorithm based illumination normalization performs well compared with existing CLAHE; it enhances the fine details of the image. ASBF-based noise filtering also provides better performance in noise removal, which sharpens the image. This way of preprocessing results in high matching results in face recognition. At the same time, existing methods such as DF and CAN attain less rank 1 score since it doesn’t use effective algorithm for preprocessing and thus reduce the quality of given image drastically. Likewise, HLD also attains less rank 1 score compared with our method. Since, it doesn’t perform illumination normalization and noise filtering also not effective. From this analysis, we conclude that our MF-AIFR attains better results in rank 1-score compared with other methods.
Comparisons on rank 1-score.
Table 10 signifies average simulation results comparison of rank 1-score with the existing and proposed methods. From the above comparison, we prove that our MF-AIFR method achieves higher rank 1 score percentage as 89.8% compared with existing methods.
Methods | Rank 1 score |
---|---|
HLD | 79.6 |
DF | 73 |
CAN | 65 |
MF-AIFR | 89.8 |
Rank 1 score comparisons [average].
Performance of the computation time is evaluated by varying the number of images. This metric must be low in order to attain better performance in image retrieval across aging.
Figure 12 depicts the comparisons on computation time results with respect to the existing methods. It is noticed that our MF-AIFR method achieves less computation time compared with the existing methods such as CAN, DF, and HLD. MF-AIFR performs IQE process before entering into the preprocessing step. The images that are not satisfying IQT only undergone preprocessing; otherwise it is directly given to the pose normalization step. Thus it reduces the time wastages in performing preprocessing for all input images. In addition to it, our work also reduces time in feature extraction and classification by using effective algorithms such as CNN, SIHKS, and SVM. These algorithms require less time to process the given inputs. As a result, MF-AIFR achieves less computation time. In the meantime, existing methods such as CAN and DF attain high computation time compared with other methods. Since it performs preprocessing for all images and also doesn’t utilize effective algorithm to process the given input image and thus leads to increase in computation time. Likewise, HLD also attains high computation time compared with MF-AIFR since it performs preprocessing for all images regardless of their quality.
Comparisons on computation time.
Table 11 deliberates the comparisons of computation time and thus shows that our method attains less computation time as 12.4ms compared with other methods including HLD, DF, and CAN.
Methods | Computation time (ms) |
---|---|
HLD | 60 |
DF | 63 |
CAN | 73 |
MF-AIFR | 12.4 |
Computation time comparisons [average].
This section signifies highlights of this research regarding face recognition across aging. In order to achieve better performance in AIFR, our work establishes five consequent processes. Table 12 describes the benefits of proposed algorithms along with their functionalities. This table illustrates each algorithm with their benefits in performance metrics such as precision, recall, accuracy, recognition rate, and rank 1 score.
Algorithms | Main functionality | Benefits related to performance |
---|---|---|
DGC-CLAHE | Illumination Normalization | Enhances the recognition rate and accuracy |
ASBF | Noise removal | Enhances recognition rate and feature extraction efficiency |
EA-AT | Pose Normalization | Easier the feature extraction process and Increases the precision level |
CNN | Texture Feature Extraction | Enhances the accuracy in face recognition across aging and perform well in large scale data set |
SIHKS | Shape & Demographic Feature extraction | Increases the rank 1-score and adapts large scale data set. |
SVM | Recognition and Interval | Simple processing, increases the accuracy and reduces the recall |
Benefits of proposed algorithms.
Face recognition across aging becomes challenging due to changes in the human faces with age progressions. In order to address this bottleneck, this chapter proposes MF-AIFR method where four successive processes performed that are listed as follows: IQE is performed to reduce time spend in preprocessing and thus enhances performance of our system drastically. An image that doesn’t satisfy the IQT is given as input to the preprocessing step. Here, illumination normalization and noise removal are performed, which enhances the accuracy in face recognition and retrieval. Illumination normalization adopts DGC-CLAHE, and noise removal adopts ASBF algorithm. In order to normalize the pose, we adopt EA-AT algorithm, which is performed to enhance the feature extraction efficacy. Two types of descriptors are utilized for features extractions that are CNN and SIHKS. Here, we extract multiple features such as texture, shape, and demographic features. We extract features from three types of regions that are periocular, nose, and mouth. CNN extracts texture features, and SIHKS extracts shape and demographic features. This way extracting features increases our recognition rate. In recognition and retrieval, we execute SVM algorithm, which follows the simple procedure and provides better results. At last, we evaluate the performance of MF-AIFR system using seven metrics that are Accuracy, Recall, Precision, Rank-1 Score, F-Score, Recognition rate, and Computation time. Thus it shows that our work performs better than existing methods such as HLD, DF, and CAN.
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All published Book Chapters are licensed under a Creative Commons Attribution 3.0 Unported License. Monographs are licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license granted to all others. Our Copyright Policy aims to guarantee that original material is published while at the same time giving significant freedom to our Authors. IntechOpen upholds a flexible Copyright Policy meaning that there is no copyright transfer to the publisher and Authors hold exclusive copyright to their work.
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In all cases, cyclical ups and downs depend not only on internal system cyclical processes and their factors in countries but also on the consequences of intercountry interaction. The ability to measure and predict business cycles, taking into account their mutual influence, is a prerequisite for the development of an adequate business policy of countries and their associations.",book:{id:"6703",slug:"statistics-growing-data-sets-and-growing-demand-for-statistics",title:"Statistics",fullTitle:"Statistics - Growing Data Sets and Growing Demand for Statistics"},signatures:"Elena Zarova",authors:null},{id:"60246",title:"Statistical Research of Investment Appeal of Russian Regions",slug:"statistical-research-of-investment-appeal-of-russian-regions",totalDownloads:981,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"In this chapter, the methodological results directed on realization statistical research of investment appeal of Russian regions are offered. 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He has an excellent track record in the herpesvirus field, and his group is engaged in clinical research in the field of Epstein-Barr virus diseases. He is the editor of the online Encyclopedia of Environment and he coordinates the Universal Health Coverage education program for the BioHealth Computing Schools of the European Institute of Science.",institutionString:null,institution:{name:"Grenoble Alpes University",country:{name:"France"}}},{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",slug:"alfonso-j.-rodriguez-morales",fullName:"Alfonso J. Rodriguez-Morales",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},{id:"332819",title:"Dr.",name:"Chukwudi Michael",middleName:"Michael",surname:"Egbuche",slug:"chukwudi-michael-egbuche",fullName:"Chukwudi Michael Egbuche",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/332819/images/14624_n.jpg",biography:"I an Dr. Chukwudi Michael Egbuche. I am a Senior Lecturer in the Department of Parasitology and Entomology, Nnamdi Azikiwe University, Awka.",institutionString:null,institution:{name:"Nnamdi Azikiwe University",country:{name:"Nigeria"}}},{id:"284232",title:"Mr.",name:"Nikunj",middleName:"U",surname:"Tandel",slug:"nikunj-tandel",fullName:"Nikunj Tandel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/284232/images/8275_n.jpg",biography:'Mr. Nikunj Tandel has completed his Master\'s degree in Biotechnology from VIT University, India in the year of 2012. He is having 8 years of research experience especially in the field of malaria epidemiology, immunology, and nanoparticle-based drug delivery system against the infectious diseases, autoimmune disorders and cancer. He has worked for the NIH funded-International Center of Excellence in Malaria Research project "Center for the study of complex malaria in India (CSCMi)" in collaboration with New York University. The preliminary objectives of the study are to understand and develop the evidence-based tools and interventions for the control and prevention of malaria in different sites of the INDIA. Alongside, with the help of next-generation genomics study, the team has studied the antimalarial drug resistance in India. Further, he has extended his research in the development of Humanized mice for the study of liver-stage malaria and identification of molecular marker(s) for the Artemisinin resistance. At present, his research focuses on understanding the role of B cells in the activation of CD8+ T cells in malaria. 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She is currently an Adjunct Professor at Feevale University in Medicine and Biomedicine courses and a permanent professor of the Academic Master\\'s Degree in Virology. She has experience in the field of Microbiology, with an emphasis on Bacteriology, working mainly on the following topics: bacteriophages, bacterial resistance, clinical microbiology and food microbiology.",institutionString:null,institution:{name:"Universidade Feevale",country:{name:"Brazil"}}},{id:"229220",title:"Dr.",name:"Amjad",middleName:"Islam",surname:"Aqib",slug:"amjad-aqib",fullName:"Amjad Aqib",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229220/images/system/229220.png",biography:"Dr. Amjad Islam Aqib obtained a DVM and MSc (Hons) from University of Agriculture Faisalabad (UAF), Pakistan, and a PhD from the University of Veterinary and Animal Sciences Lahore, Pakistan. Dr. Aqib joined the Department of Clinical Medicine and Surgery at UAF for one year as an assistant professor where he developed a research laboratory designated for pathogenic bacteria. Since 2018, he has been Assistant Professor/Officer in-charge, Department of Medicine, Manager Research Operations and Development-ORIC, and President One Health Club at Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan. He has nearly 100 publications to his credit. His research interests include epidemiological patterns and molecular analysis of antimicrobial resistance and modulation and vaccine development against animal pathogens of public health concern.",institutionString:"Cholistan University of Veterinary and Animal Sciences",institution:null},{id:"62900",title:"Prof.",name:"Fethi",middleName:null,surname:"Derbel",slug:"fethi-derbel",fullName:"Fethi Derbel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62900/images/system/62900.jpeg",biography:"Professor Fethi Derbel was born in 1960 in Tunisia. He received his medical degree from the Sousse Faculty of Medicine at Sousse, University of Sousse, Tunisia. He completed his surgical residency in General Surgery at the University Hospital Farhat Hached of Sousse and was a member of the Unit of Liver Transplantation in the University of Rennes, France. He then worked in the Department of Surgery at the Sahloul University Hospital in Sousse. Professor Derbel is presently working at the Clinique les Oliviers, Sousse, Tunisia. His hospital activities are mostly concerned with laparoscopic, colorectal, pancreatic, hepatobiliary, and gastric surgery. He is also very interested in hernia surgery and performs ventral hernia repairs and inguinal hernia repairs. He has been a member of the GREPA and Tunisian Hernia Society (THS). During his residency, he managed patients suffering from diabetic foot, and he was very interested in this pathology. For this reason, he decided to coordinate a book project dealing with the diabetic foot. Professor Derbel has published many articles in journals and collaborates intensively with IntechOpen Access Publisher as an editor.",institutionString:"Clinique les Oliviers",institution:null},{id:"300144",title:"Dr.",name:"Meriem",middleName:null,surname:"Braiki",slug:"meriem-braiki",fullName:"Meriem Braiki",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/300144/images/system/300144.jpg",biography:"Dr. Meriem Braiki is a specialist in pediatric surgeon from Tunisia. She was born in 1985. She received her medical degree from the University of Medicine at Sousse, Tunisia. She achieved her surgical residency training periods in Pediatric Surgery departments at University Hospitals in Monastir, Tunis and France.\r\nShe is currently working at the Pediatric surgery department, Sidi Bouzid Hospital, Tunisia. Her hospital activities are mostly concerned with laparoscopic, parietal, urological and digestive surgery. She has published several articles in diffrent journals.",institutionString:"Sidi Bouzid Regional Hospital",institution:null},{id:"229481",title:"Dr.",name:"Erika M.",middleName:"Martins",surname:"de Carvalho",slug:"erika-m.-de-carvalho",fullName:"Erika M. de Carvalho",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229481/images/6397_n.jpg",biography:null,institutionString:null,institution:{name:"Oswaldo Cruz Foundation",country:{name:"Brazil"}}},{id:"186537",title:"Prof.",name:"Tonay",middleName:null,surname:"Inceboz",slug:"tonay-inceboz",fullName:"Tonay Inceboz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/186537/images/system/186537.jfif",biography:"I was graduated from Ege University of Medical Faculty (Turkey) in 1988 and completed his Med. PhD degree in Medical Parasitology at the same university. I became an Associate Professor in 2008 and Professor in 2014. 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She studied for her doctoral degree, at the Department of Entomology, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, USA. She has completed her Ph.D. degrees in Parasitology in Egypt, from where she got the award for “the best scientific Ph.D. dissertation”. She worked at the School of Biological Sciences, Bristol, England, the UK in controlling insects of medical and veterinary importance as a grant from Newton Mosharafa, the British Council. Her research is focused on searching of pesticides against mosquitoes, house flies, lice, green bottle fly, camel nasal botfly, soft and hard ticks, mites, and the diamondback moth as well as control of several parasites using safe and natural materials to avoid drug resistances and environmental contamination.",institutionString:null,institution:{name:"Banha University",country:{name:"Egypt"}}},{id:"99780",title:"Prof.",name:"Omolade",middleName:"Olayinka",surname:"Okwa",slug:"omolade-okwa",fullName:"Omolade Okwa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/99780/images/system/99780.jpg",biography:"Omolade Olayinka Okwa is presently a Professor of Parasitology at Lagos State University, Nigeria. She has a PhD in Parasitology (1997), an MSc in Cellular Parasitology (1992), and a BSc (Hons) Zoology (1990) all from the University of Ibadan, Nigeria. She teaches parasitology at the undergraduate and postgraduate levels. She was a recipient of a Commonwealth fellowship supported by British Council tenable at the Centre for Entomology and Parasitology (CAEP), Keele University, United Kingdom between 2004 and 2005. She was awarded an Honorary Visiting Research Fellow at the same university from 2005 to 2007. \nShe has been an external examiner to the Department of Veterinary Microbiology and Parasitology, University of Ibadan, MSc programme between 2010 and 2012. She is a member of the Nigerian Society of Experimental Biology (NISEB), Parasitology and Public Health Society of Nigeria (PPSN), Science Association of Nigeria (SAN), Zoological Society of Nigeria (ZSN), and is Vice Chairperson of the Organisation of Women in Science (OWSG), LASU chapter. She served as Head of Department of Zoology and Environmental Biology, Lagos State University from 2007 to 2010 and 2014 to 2016. She is a reviewer for several local and international journals such as Unilag Journal of Science, Libyan Journal of Medicine, Journal of Medicine and Medical Sciences, and Annual Research and Review in Science. \nShe has authored 45 scientific research publications in local and international journals, 8 scientific reviews, 4 books, and 3 book chapters, which includes the books “Malaria Parasites” and “Malaria” which are IntechOpen access publications.",institutionString:"Lagos State University",institution:{name:"Lagos State University",country:{name:"Nigeria"}}},{id:"273100",title:"Dr.",name:"Vijay",middleName:null,surname:"Gayam",slug:"vijay-gayam",fullName:"Vijay Gayam",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/273100/images/system/273100.jpeg",biography:"Dr. Vijay Bhaskar Reddy Gayam is currently practicing as an internist at Interfaith Medical Center in Brooklyn, New York, USA. 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Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. 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