Advances in Image and Video Segmentation

Yu-Jin ZHANG (Editor)

IRM Press, USA£¬2006

Copyright @2006 by Idea Group Inc.

ISBN 1-59140-753-2 (hard-cover, US$89.95)
ISBN 1-59140-754-0 (soft-cover, US$74.95)
ISBN 1-59140-755-9 (ebook)

457 pages     More information-1  More information-2

Introduction

 (Selected from "Preface")

Image and video segmentation is one of the most critical tasks of image and video analysis which has the objective of extracting information (represented by data) from an image or a sequence of images (video). In the last 40 years, this field has experienced significant growth and progress, resulting in a virtual explosion of published information.

The field of image and video segmentation is still a very hot topic, with much advancement in recent years. As a consequence, there is a considerable need for books like this one, which attempts to bring together a selection of the latest results from researchers involved in state-of-the-art work in image and video segmentation.

This book is intended for scientists and engineers who are engaged in research and development in image and video segmentation and who wish to keep their paces with the advances of this field. Comprehensive coverage of various branches of image and video segmentation is provided by more than 50 experts around the world. The book includes 20 chapters and they are organized into six sections.

Section I is for the purpose of providing some background information, which consists of one introductory survey chapter (Chapter 1).

Section II is focused on image segmentation, which consists of four chapters (Chapter II through V) showing the advances of image segmentation by using optimization, variational model, meta-heuristic, and dynamical systems.

Section III is focused on video segmentation, which consists of four chapters (Chapter VI through IX) showing the advances of video segmentation in mean shift-based filtering, video object segmentation, active shape model, and shot boundary detection.

Section IV consists of four chapters (Chapter X through XIII) presenting several new algorithms for segmenting particular types of images, such as color, texture, 3-D medical, and multi-channel images.

Section V contains four chapters (Chapter XIV through XVII) depicting various applications of segmentation techniques to fresh areas, such as human lip segmentation, machine-printed character segmentation, food image segmentation and blind navigation.

Section VI presents higher level topic of segmentation evaluation, which consists of three chapters (Chapter XVIII through XX). Unsupervised and supervised evaluations, objective video evaluation, as well as a summary of recent evaluation progresses are presented.

Contents

 http://www.loc.gov/catdir/toc/ecip0610/2006009296.html

Section I    Introduction
   Chapter 1   An Overview of Image and Video Segmentation in the Last 40 Years

Section II   Image Segmentation
   Chapter 2   Optimal Image Segmentation Methods based on Energy Minimization
   Chapter 3   Variational Problems in Image Segmentation and Convergence Methods
   Chapter 4   A Graph-Based Image Segmentation Algorithm Using Hierarchical Social Metaheuristic
   Chapter 5   Modeling Complex Dynamical Systems for Image Segmentation

Section III   Video Segmentation
   Chapter 6   Joint Space-Time-Range Mean Shift-Based Image and Video Segmentation
   Chapter 7   Fast Automatic Video Object Segmentation for Content-based Applications
   Chapter 8   A Fully Automated Active Shape Model for Segmentation and Tracking of 
 	      Unknown Objects in a Cluttered Environment
   Chapter 9   Video Shot Boundary Detection and Scene Segmentation

Section IV   Segmenting Particular Images
   Chapter 10   Color Image Segmentation in both Feature and Image Spaces
   Chapter 11   Optimising Texture Primitives Description, Analysis, Segmentation and 
 	       Classification Using Variography
   Chapter 12   Methods and Applications for Segmenting 3D Medical Image Data
   Chapter 13   Parallel Segmentation of Multichannel Images Using Multidimensional 
 	       Mathematical Morphology

Section V    Special Segmentation Applications
   Chapter 14   Fuzzy Clustering-Based Approaches for Automatic Lip Segmentation from Color Images
   Chapter 15   Mathematical Morphology Based Automatic Restoration and Segmentation for Degraded 
 	       Machine-Printed Character Images
   Chapter 16   Segmentation in Food Images
   Chapter 17   Segmentation via Thresholding Methodologies by Using Measure of Fuzziness 
 	       Towards Blind Navigation

Section VI   Segmentation Evaluation
   Chapter 18   Unsupervised and Supervised Segmentation Evaluation
   Chapter 19   Objective Evaluation of Video Segmentation Quality
   Chapter 20   Summary of Recent Progresses for Segmentation Evaluation

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