Metaheuristic Algorithms For Image Segmentation Theory And Applications

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Metaheuristic Algorithms for Image Segmentation: Theory and Applications

Metaheuristic Algorithms for Image Segmentation: Theory and Applications
Author :
Publisher : Springer
Total Pages : 229
Release :
ISBN-10 : 9783030129316
ISBN-13 : 3030129314
Rating : 4/5 (314 Downloads)

Book Synopsis Metaheuristic Algorithms for Image Segmentation: Theory and Applications by : Diego Oliva

Download or read book Metaheuristic Algorithms for Image Segmentation: Theory and Applications written by Diego Oliva and published by Springer. This book was released on 2019-03-02 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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