Metaheuristic Algorithms for Image Segmentation: Theory and Applications

• Main Authors: Oliva, Diego (Author, http://id.loc.gov/vocabulary/relators/aut), Abd Elaziz, Mohamed (http://id.loc.gov/vocabulary/relators/aut), Hinojosa, Salvador (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Studies in Computational Intelligence, 825
• Subjects: Computational intelligence.; Artificial intelligence.; Signal processing.; Image processing.; Speech processing systems.; Computational Intelligence.; Artificial Intelligence.; Signal, Image and Speech Processing.

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 implem...

Table of Contents:

• Introduction
• Optimization
• Metaheuristic optimization
• Image processing
• Image Segmentation using metaheuristics
• Multilevel thresholding for image segmentation based on metaheuristic Algorithms
• Otsu's between class variance and the tree seed algorithm
• Image segmentation using Kapur's entropy and a hybrid optimization algorithm
• Tsallis entropy for image thresholding
• Image segmentation with minimum cross entropy
• Fuzzy entropy approaches for image segmentation
• Image segmentation by gaussian mixture
• Image segmentation as a multiobjective optimization problem
• Clustering algorithms for image segmentation
• Contextual information in image thresholding.