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Hybrid Soft Computing for Image Segmentation / edited by Siddhartha Bhattacharyya, Paramartha Dutta, Sourav De, Goran Klepac.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Bhattacharyya, Siddhartha, 1975- editor.
Dutta, Paramartha, editor.
De, Sourav, editor.
Klepac, Goran, 1972- editor.
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
Language:
English
Subjects (All):
Artificial intelligence.
Computational intelligence.
Optical data processing.
Artificial Intelligence.
Computational Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Local Subjects:
Artificial Intelligence.
Computational Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Physical Description:
1 online resource (XVI, 321 pages) : 162 illustrations, 87 illustrations in color
Edition:
First edition 2016.
Contained In:
Springer eBooks
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2016.
System Details:
text file PDF
Summary:
This book proposes soft computing techniques for segmenting real-life images in applications such as image processing, image mining, video surveillance, and intelligent transportation systems. The book suggests hybrids deriving from three main approaches: fuzzy systems, primarily used for handling real-life problems that involve uncertainty; artificial neural networks, usually applied for machine cognition, learning, and recognition; and evolutionary computation, mainly used for search, exploration, efficient exploitation of contextual information, and optimization. The contributed chapters discuss both the strengths and the weaknesses of the approaches, and the book will be valuable for researchers and graduate students in the domains of image processing and computational intelligence.
Contents:
Hybrid Soft Computing Techniques for Image Segmentation: Fundamentals and Applications
Enhanced Rough-Fuzzy C-Means Algorithm for Image Segmentation
Intuitionistic Fuzzy C-means Clustering Algorithm for Brain Image Segmentation
Automatic Segmentation Approaches
Modified Level Set Segmentation
Fuzzy Deformable Models for 3D Segmentation of Brain Structures
Rough Sets for Probabilistic Model Based Image Segmentation
Segmentation of Cerebral Images. .
Other Format:
Printed edition:
ISBN:
978-3-319-47223-2
9783319472232
Access Restriction:
Restricted for use by site license.

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