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Applications of Hybrid Metaheuristic Algorithms for Image Processing

Categories: Science, Engineering
Event Date: 2019-11-30 Abstract Due: 2019-06-30

Call for Book Chapters
Applications of Hybrid Metaheuristic Algorithms for Image Processing
To be published by Studies in Computational Intelligence by Springer http://www.springer.com/series/7092


The segmentation of images is a critical task for computer vision applications. The objective is to generate segmented images as fast and accurate as possible. However, due to the complex nature of digital images, the segmentation is not a trivial task. Metaheuristic Algorithms (MA) have been used to perform image segmentation over the last decade with interesting results. Usually, MAs can behave in two forms; exploration, and exploitation. The exploration phase is used to diversify the solutions along the search space to avoid local stagnation, while the exploitation phase intensifies the search in a region to ensure convergence. The performance of many MAs is limited by its operators. In some cases, the operators that control the algorithm have proved to be very efficient, but its interaction with different approaches can further enhance its performance.  The hybridization of MAs is a new tendency where two or more algorithms are merged to generate better results. Usually, the hybridization can take two forms; sequential use of algorithms, and the replacement of operators. In the first case, two MA are run in sequence to firstly explore with an algorithm and then perform exploitation on the later; however, this approach can significantly increase the number of iterations required to converge. In the second case, the operators of two or more algorithms are mixed together provide a better balance between the intensification and diversification of the solutions without increasing the number of iterations.

This Book aims to provide a collection of high-quality research works that address broad challenges in both theoretical and application aspects of hybrid metaheuristic algorithms in image processing and computer vision. We invite colleagues to contribute original book chapters that will stimulate the continuing effort on the application of hybrid MAs approaches to solve image-processing problems and computer vision problems.

We invite all researchers and practitioners who are developing algorithms, systems, and applications, to share their results, ideas, and experiences.

Topics of interest include, but are not limited to, the following:

 Hybrid Metaheuristics
Theoretical aspects of hybridization
Automated parameter tuning
Evolutionary Computation Algorithms
Swarm Optimization
Multi-objective optimization
Multilevel segmentation
Object recognition
Computer vision
Image processing
Filtering and enhancement
Edge detection and segmentation
Feature extraction
Quantum Image Processing
Image thresholding
Chapter Submission

Submitted manuscripts should conform to the standard guidelines of the Springer’s book chapter format. Manuscripts must be prepared using Latex or Word according to the Springer’s template that can be downloaded from the (link). Manuscripts that do not follow the formatting rules will be ignored. Prospective authors should send their manuscripts electronically to the following email address: salvahin@ucm.es and/or doliva@ucm.es ,  with the subject title as: “Applications of Hybrid Metaheuristic Algorithms for Image Processing – Book Chapter” in PDF. Submitted manuscripts will be refereed by at least two independent and expert reviewers for quality, correctness, originality, and relevance. The accepted contributions will be published in Intelligent Systems Reference Library by Springer. More information about Intelligent Systems Reference Library can be found (here).

Publication Schedule

The tentative schedule of the book publication is as follows:

Deadline for paper submission: June 30, 2019
First round notification: August 2019
Camera-ready submission: September 2019
Publication date: 1st quarter of 2020

Volume Editors

Diego Oliva

Departamento de Ciencias Computacionales, Universidad de Guadalajara, CUCEI, México  diego.oliva@cucei.udg.mx, doliva@ucm.es

Salvador Hinojosa

Facultad de Informática, Universidad Complutense de Madrid, Madrid, Spain  salvahin@ucm.es



Diego Oliva