Metaheuristic Algorithms for Image Segmentation: Theory and Applications

Description

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. Front Matter ....Pages i-xv Introduction (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 1-5 Optimization (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 7-11 Metaheuristic Optimization (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 13-26 Image Processing (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 27-45 Image Segmentation Using Metaheuristics (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 47-58 Multilevel Thresholding for Image Segmentation Based on Metaheuristic Algorithms (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 59-69 Otsu’s Between Class Variance and the Tree Seed Algorithm (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 71-83 Image Segmentation Using Kapur’s Entropy and a Hybrid Optimization Algorithm (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 85-99 Tsallis Entropy for Image Thresholding (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 101-123 Image Segmentation with Minimum Cross Entropy (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 125-139 Fuzzy Entropy Approaches for Image Segmentation (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 141-147 Image Segmentation by Gaussian Mixture (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 149-155 Image Segmentation as a Multiobjective Optimization Problem (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 157-179 Clustering Algorithms for Image Segmentation (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 181-189 Contextual Information in Image Thresholding (Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa)....Pages 191-226