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© 2020

Applications of Hybrid Metaheuristic Algorithms for Image Processing

  • Diego Oliva
  • Salvador Hinojosa
Book

Part of the Studies in Computational Intelligence book series (SCI, volume 890)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Hybrid Metaheuristics and Image Segmentation

    1. Front Matter
      Pages 1-1
    2. Mario A. Navarro, Gustavo R. Hernández, Daniel Zaldívar, Noé Ortega-Sanchez, Gonzalo Pajares
      Pages 3-26
    3. Alfonso Ramos-Michel, Marco Pérez-Cisneros, Erik Cuevas, Daniel Zaldivar
      Pages 27-51
    4. V. Saravana Kumar, E. R. Naganathan, S. Anantha Sivaprakasam, M. Kavitha
      Pages 81-103
    5. Andrea A. Hernandez del Rio, Erik Cuevas, Daniel Zaldivar
      Pages 121-149
  3. Hybrid Metaheuristics and Other Image Processing Tasks

    1. Front Matter
      Pages 151-151
    2. Gemma Corona, Marco Pérez-Cisneros, Oscar Maciel-Castillo, Adrián González, Fernando Fausto
      Pages 153-166
    3. Noé Ortega-Sánchez, Erik Cuevas, Marco A. Pérez, Valentín Osuna-Enciso
      Pages 187-203
    4. T. Hoang Ngan Le, Khoa Luu, Chi Nhan Duong, Kha Gia Quach, Thanh Dat Truong, Kyle Sadler et al.
      Pages 231-260
    5. Miguel Islas Toski, Karla Avila-Cardenas, Jorge Gálvez
      Pages 261-284
    6. Essam H. Houssein, Ibrahim E. Mohamed, Yaser M. Wazery
      Pages 285-308
  4. Health Applications

    1. Front Matter
      Pages 309-309
    2. Erick Rodrí­guez-Esparza, Laura A. Zanella-Calzada, Daniel Zaldivar, Carlos E. Galván-Tejada
      Pages 351-374
    3. Karla Avila-Cardenas, Marco Pérez-Cisneros
      Pages 375-398

About this book

Introduction

This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing.

The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.

Keywords

Image Processing Optimization Metaheuristics Thresholding Machine Learning Evolutionary Computation HMA

Editors and affiliations

  • Diego Oliva
    • 1
  • Salvador Hinojosa
    • 2
  1. 1.CUCEIUniversity of GuadalajaraGuadajalaraMexico
  2. 2.CUCEIUniversity of GuadalajaraGuadajalaraMexico

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