Description: Metaheuristic Algorithms for Image Segmentation: Theory and Applications by Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa 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. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher 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 designedto 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. Back Cover 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. Table of Contents Introduction.- Optimization.- Metaheuristic optimization.- Image processing.- Image Segmentation using metaheuristics.- Multilevel thresholding for image segmentation based on metaheuristic Algorithms.- Otsus between class variance and the tree seed algorithm.- Image segmentation using Kapurs 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. Feature Provides the most representative tools used for image segmentation Examines the theory and application of metaheuristics algorithms for the segmentation of images from diverse sources Presents a compendium of methods useful for students, scientists and practitioners Includes self-contained chapters that explain the algorithm used, the selected problem, and the implementation Offers practical examples, comparisons, and experimental results Focuses on lightweight segmentation methods based on thresholding techniques using metaheuristics algorithms (MA) to perform the pre-processing step for CVS Details ISBN3030129330 Author Salvador Hinojosa Pages 226 Language English Year 2020 ISBN-10 3030129330 ISBN-13 9783030129330 Format Paperback Series Number 825 Publication Date 2020-08-14 UK Release Date 2020-08-14 Edition 1st Place of Publication Cham Country of Publication Switzerland Illustrations 43 Illustrations, color; 15 Illustrations, black and white; XV, 226 p. 58 illus., 43 illus. in color. Publisher Springer Nature Switzerland AG Edition Description 1st ed. 2019 Series Studies in Computational Intelligence Imprint Springer Nature Switzerland AG Alternative 9783030129309 DEWEY 006.3 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:129546752;
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ISBN-13: 9783030129330
Book Title: Metaheuristic Algorithms for Image Segmentation: Theory and Appli
Number of Pages: 226 Pages
Publication Name: Metaheuristic Algorithms for Image Segmentation: Theory and Applications
Language: English
Publisher: Springer Nature Switzerland Ag
Item Height: 235 mm
Subject: Engineering & Technology, Computer Science
Publication Year: 2020
Type: Textbook
Item Weight: 379 g
Author: Salvador Hinojosa, Diego Oliva, Mohamed Abd Elaziz
Item Width: 155 mm
Format: Paperback
