Hybrid Soft Computing for Image Segmentation

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 r...

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Bibliographic Details
Call Number:Libro Electrónico
Corporate Author: SpringerLink (Online service)
Other Authors: Bhattacharyya, Siddhartha (Editor), Dutta, Paramartha (Editor), De, Sourav (Editor), Klepac, Goran (Editor)
Format: Electronic eBook
Language:Inglés
Published: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edition:1st ed. 2016.
Subjects:
Artificial intelligence.
Computational intelligence.
Image processing-Digital techniques.
Computer vision.
Artificial Intelligence.
Computational Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Online Access:Texto Completo
Table of 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. .

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