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Interactive Segmentation Techniques

Algorithms and Performance Evaluation

  • Jia He
  • Chang-Su Kim
  • C.-C. Jay Kuo

Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Also part of the SpringerBriefs in Signal Processing book sub series (BRIEFSSIGNAL)

Table of contents

  1. Front Matter
    Pages i-x
  2. Jia He, Chang-Su Kim, C.-C. Jay Kuo
    Pages 1-5
  3. Jia He, Chang-Su Kim, C.-C. Jay Kuo
    Pages 7-16
  4. Jia He, Chang-Su Kim, C.-C. Jay Kuo
    Pages 17-62
  5. Jia He, Chang-Su Kim, C.-C. Jay Kuo
    Pages 63-73
  6. Jia He, Chang-Su Kim, C.-C. Jay Kuo
    Pages 75-76

About this book

Introduction

This book focuses on interactive segmentation techniques, which have been extensively studied in recent decades. Interactive segmentation emphasizes clear extraction of objects of interest, whose locations are roughly indicated by human interactions based on high level perception. This book will first introduce classic graph-cut segmentation algorithms and then discuss state-of-the-art techniques, including graph matching methods, region merging and label propagation, clustering methods, and segmentation methods based on edge detection. A comparative analysis of these methods will be provided with quantitative and qualitative performance evaluation, which will be illustrated using natural and synthetic images. Also, extensive statistical performance comparisons will be made. Pros and cons of these interactive segmentation methods will be pointed out, and their applications will be discussed.

There have been only a few surveys on interactive segmentation techniques, and those surveys do not cover recent state-of-the art techniques. By providing comprehensive up-to-date survey on the fast developing topic and the performance evaluation, this book can help readers learn interactive segmentation techniques quickly and thoroughly.

Keywords

Boundary Detection Clustering Methods Graph Matching Graph-cut Segmentation Algorithms Image Understanding Interactive Image Segmentation Label Propagation Object Extraction Region Merging

Authors and affiliations

  • Jia He
    • 1
  • Chang-Su Kim
    • 2
  • C.-C. Jay Kuo
    • 3
  1. 1.Dept. of Electrical EngineeringUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.School of Electrical EngineeringKorea UniversitySeoulKorea, Republic of (South Korea)
  3. 3.Dept. of Electrical Engineering Dept. of Computer ScienceUniversity of Southern CaliforniaArcadiaUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-4451-60-4
  • Copyright Information The Author(s) 2014
  • Publisher Name Springer, Singapore
  • eBook Packages Engineering
  • Print ISBN 978-981-4451-59-8
  • Online ISBN 978-981-4451-60-4
  • Series Print ISSN 2191-8112
  • Series Online ISSN 2191-8120
  • Buy this book on publisher's site