عنوان

Metaheuristic algorithms for image segmentation :

(Number (ISBN

3030129314

(Number (ISBN

3030129322

(Number (ISBN

3030129330

(Number (ISBN

9783030129316

(Number (ISBN

9783030129323

(Number (ISBN

9783030129330

Erroneous ISBN

3030129306

Erroneous ISBN

9783030129309

Title Proper

Metaheuristic algorithms for image segmentation :

General Material Designation

[Book]

Other Title Information

theory and applications /

First Statement of Responsibility

Diego Oliva, Mohamed Abd Elaziz, Salvador Hinojosa.

Place of Publication, Distribution, etc.

Cham, Switzerland :

Name of Publisher, Distributor, etc.

Springer,

Date of Publication, Distribution, etc.

2019.

Specific Material Designation and Extent of Item

1 online resource (xv, 226 pages) :

Other Physical Details

illustrations (some color).

Series Title

Studies in computational intelligence,

Volume Designation

volume 825

ISSN of Series

1860-949X ;

Text of Note

Includes bibliographical references.

Text of Note

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.

0

Text of Note

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.

Source for Acquisition/Subscription Address

Springer Nature

Stock Number

com.springer.onix.9783030129316

International Standard Book Number

9783030129309

Evolutionary computation.

Image segmentation.

Evolutionary computation.

Image segmentation.

COM004000

UYQ

UYQ

Number

Edition

Class number

Oliva, Diego

Abd Elaziz, Mohamed

Hinojosa, Salvador

Date of Transaction

20200823083103.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y