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This book is indexed in
Medicine » Cardiology and Cardiovascular Medicine
Image Segmentation
Edited by Pei-Gee Ho, ISBN 978-953-307-228-9, Hard cover, 538 pages, Publisher: InTech, Chapters published April 19, 2011 under CC BY-NC-SA 3.0 license
DOI: 10.5772/628
It was estimated that 80% of the information received by human is visual. Image processing is evolving fast and continually. During the past 10 years, there has been a significant research increase in image segmentation. To study a specific object in an image, its boundary can be highlighted by an image segmentation procedure. The objective of the image segmentation is to simplify the representation of pictures into meaningful information by partitioning into image regions. Image segmentation is a technique to locate certain objects or boundaries within an image. There are many algorithms and techniques have been developed to solve image segmentation problems, the research topics in this book such as level set, active contour, AR time series image modeling, Support Vector Machines, Pixon based image segmentations, region similarity metric based technique, statistical ANN and JSEG algorithm were written in details. This book brings together many different aspects of the current research on several fields associated to digital image segmentation. Four parts allowed gathering the 27 chapters around the following topics: Survey of Image Segmentation Algorithms, Image Segmentation methods, Image Segmentation Applications and Hardware Implementation. The readers will find the contents in this book enjoyable and get many helpful ideas and overviews on their own study.
- Chapter 1
A Survey of Image Segmentation by the Classical Method and Resonance Algorithm - Chapter 2
A Review of Algorithms for Segmentation of Retinal Image Data Using Optical Coherence Tomography - Chapter 3
Image Segmentation through Clustering Based on Natural Computing Techniques - Chapter 4
Segmentation with Learning Automata - Chapter 5
Surround Suppression and Recurrent Interactions V1-V2 for Natural Scene Boundary Detection - Chapter 6
Using Emergence Phenomenon in Meaningful Image Segmentation for Content-based Image Retrieval - Chapter 7
Dual Active Contour Models for Medical Image Segmentation - Chapter 8
Image Segmentation Using Maximum Spanning Tree on Affinity Matrix - Chapter 9
Image Segmentation by Autoregressive Time Series Model - Chapter 10
Evolutionary-based Image Segmentation Methods - Chapter 11
Segmentation of Handwritten Document Images into Text Lines - Chapter 12
IR Image Segmentation by Combining Genetic Algorithm and Multi-scale Edge Detection - Chapter 13
Segmentation of Remotely Sensed Imagery: Moving from Sharp Objects to Fuzzy Regions - Chapter 14
Color-based Texture Image Segmentation for Vehicle Detection - Chapter 15
An Enhanced Level Set Algorithm for Wrist Bone Segmentation - Chapter 16
Mineral Grain Boundary Detection With Image Processing Method: From Edge Detection Operation To Level Set Technique - Chapter 17
Multiscale Segmentation Techniques for Textile Images - Chapter 18
JSEG Algorithm and Statistical ANN Image Segmentation Techniques for Natural Scenes - Chapter 19
Image Segmentation of Ziehl-Neelsen Sputum Slide Images for Tubercle Bacilli Detection - Chapter 20
Image Segmentation Based on a Two-Dimensional Histogram - Chapter 21
Segmentation Methods for Biomedical Images - Chapter 22
Algorithm Selection Based on a Region Similarity Metric for Intracellular Image Segmentation - Chapter 23
Extraction of Estuarine/Coastal Environmental Bodies from Satellite Data through Image Segmentation Techniques - Chapter 24
Rock Fracture Image Segmentation Algorithms - Chapter 25
Image Segmentation Integrating Generative and Discriminative Methods - Chapter 26
Pixon-Based Image Segmentation - Chapter 27
Hardware Implementation of a Real-Time Image Segmentation Circuit based on Fuzzy Logic for Edge Detection Application


