Open access peer-reviewed Edited Volume

Advances in Object Recognition Systems

Edited by Ioannis Kypraios

Oxford University Press (United Kingdom), United Kingdom

An invariant object recognition system needs to be able to recognise the object under any usual a priori defined distortions such as translation, scaling and in-plane and out-of-plane rotation. Ideally, the system should be able to recognise (detect and classify) any complex scene of objects even within background clutter noise. In this book, we present recent advances towards achieving fully-robust object recognition. The relation and importance of object recognition in the cognitive processes of humans and animals is described as well as how human- and animal-like cognitive processes can be used for the design of biologically-inspired object recognition systems. Colour processing is discussed in the development of fully-robust object recognition systems. Examples of two main categories of object recognition systems, the optical correlators and pure artificial neural network architectures, are given. Finally, two examples of object recognition's applications are described in details. With the recent technological advancements object recognition becomes widely popular with existing applications in medicine for the study of human learning and memory, space science and remote sensing for image analysis, mobile computing and augmented reality, semiconductors industry, robotics and autonomous mobile navigation, public safety and urban management solutions and many more others. This book is a "must-read" for everyone with a core or wider interest in this "hot" area of cutting-edge research.

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Advances in Object Recognition SystemsEdited by Ioannis Kypraios

Published: May 9th 2012

DOI: 10.5772/2392

ISBN: 978-953-51-0598-5

eBook (PDF) ISBN: 978-953-51-5646-8

Copyright year: 2012

Books open for chapter submissions

14056 Total Chapter Downloads

9 Crossref Citations

9 Web of Science Citations

11 Dimensions Citations

chaptersDownloads

Open access peer-reviewed

1. Neural Basis of Object Recognition

By R. Marra, D. Rotiroti and V. Rispoli

1424

Open access peer-reviewed

2. Spontaneous Object Recognition in Animals: A Test of Episodic Memory

By Amy-Lee Kouwenberg, Gerard M. Martin, Darlene M. Skinner, Christina M. Thorpe and Carolyn J. Walsh

2161

Open access peer-reviewed

3. Performance Analysis of the Modified-Hybrid Optical Neural Network Object Recognition System Within Cluttered Scenes

By Ioannis Kypraios

933

Open access peer-reviewed

4. The Contribution of Color to Object Recognition

By Inês Bramão, Luís Faísca, Karl Magnus Petersson and Alexandra Reis

2116

Open access peer-reviewed

5. Advances in Adaptive Composite Filters for Object Recognition

By Victor H. Diaz-Ramirez, Leonardo Trujillo and Sergio Pinto-Fernandez

1220

Open access peer-reviewed

6. The Use of Contour, Shape and Form in an Integrated Neural Approach for Object Recognition

By I. Lopez-Juarez

1326

Open access peer-reviewed

7. Automatic Coin Classification and Identification

By Reinhold Huber-Mörk, Michael Nölle, Michael Rubik, Michael Hödlmoser, Martin Kampel and Sebastian Zambanini

3794

Open access peer-reviewed

8. Non-Rigid Objects Recognition: Automatic Human Action Recognition in Video Sequences

By Mehrez Abdellaoui, Ali Douik and Kamel Besbes

1083

Edited Volume and chapters are indexed in

  • Worldcat
  • OpenAIRE
  • Google Scholar
  • AZ ebsco
  • Base
  • CNKI

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