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Metaheuristic Algorithms for Image Segmentation: Theory and Applications

  • Diego Oliva
  • Mohamed Abd Elaziz
  • Salvador Hinojosa

Part of the Studies in Computational Intelligence book series (SCI, volume 825)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 1-5
  3. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 7-11
  4. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 13-26
  5. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 27-45
  6. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 47-58
  7. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 59-69
  8. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 71-83
  9. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 85-99
  10. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 101-123
  11. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 125-139
  12. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 141-147
  13. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 149-155
  14. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 157-179
  15. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 181-189
  16. Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa
    Pages 191-226

About this book

Introduction

This book presents a study of the most important methods of image segmentation and how they are extended and improved using metaheuristic algorithms. The segmentation approaches selected have been extensively applied to the task of segmentation (especially in thresholding), and have also been implemented using various metaheuristics and hybridization techniques leading to a broader understanding of how image segmentation problems can be solved from an optimization perspective. The field of image processing is constantly changing due to the extensive integration of cameras in devices; for example, smart phones and cars now have embedded cameras. The images have to be accurately analyzed, and crucial pre-processing steps, like image segmentation, and artificial intelligence, including metaheuristics, are applied in the automatic analysis of digital images. Metaheuristic algorithms have also been used in various fields of science and technology as the demand for new methods designed to solve complex optimization problems increases.
This didactic book is primarily intended for undergraduate and postgraduate students of science, engineering, and computational mathematics. It is also suitable for courses such as artificial intelligence, advanced image processing, and computational intelligence. The material is also useful for researches in the fields of evolutionary computation, artificial intelligence, and image processing.

Keywords

Image Processing Optimization Metaheuristics Thresholding Machine Learning Evolutionary Computation

Authors and affiliations

  • Diego Oliva
    • 1
  • Mohamed Abd Elaziz
    • 2
  • Salvador Hinojosa
    • 3
  1. 1.Departamento de Electrónica, CUCEIUniversidad de GuadalajaraGuadalajaraMexico
  2. 2.Faculty of ScienceZagazig UniversityZagazigEgypt
  3. 3.Facultad de InformáticaUniversidad Complutense de MadridMadridSpain

Bibliographic information