Rough Fuzzy Image Analysis : Foundations and Methodologies

Sankar K. Pal

ISBN 10: 1439803293 / ISBN 13: 9781439803295

Published by Taylor & Francis Inc Mai 2010, 2010

About this Item

Neuware - Emphasizing the utility of fuzzy, near, and rough sets in image analysis, 'Rough Fuzzy Image Analysis' introduces the fundamentals and applications in the state of the art of this type of image analysis.

Seller Inventory # 9781439803295

Bibliographic Details

• Title: Rough Fuzzy Image Analysis : Foundations and Methodologies
• Publisher: Taylor & Francis Inc Mai 2010
• Publication Date: 2010
• Language: English
• ISBN 10: 1439803293
• ISBN 13: 9781439803295
• Binding: Buch
• Condition: Neu
• Dimensions: 264W x 184H x 19D millimeters 264 millimeters width by 184 millimeters height by 19 millimeters depth
• Weight: 678 grams

About this title

Synopsis

Fuzzy sets, near sets, and rough sets are useful and important stepping stones in a variety of approaches to image analysis. These three types of sets and their various hybridizations provide powerful frameworks for image analysis. Emphasizing the utility of fuzzy, near, and rough sets in image analysis, Rough Fuzzy Image Analysis: Foundations and Methodologies introduces the fundamentals and applications in the state of the art of rough fuzzy image analysis.

In the first chapter, the distinguished editors explain how fuzzy, near, and rough sets provide the basis for the stages of pictorial pattern recognition: image transformation, feature extraction, and classification. The text then discusses hybrid approaches that combine fuzzy sets and rough sets in image analysis, illustrates how to perform image analysis using only rough sets, and describes tolerance spaces and a perceptual systems approach to image analysis. It also presents a free, downloadable implementation of near sets using the Near Set Evaluation and Recognition (NEAR) system, which visualizes concepts from near set theory. In addition, the book covers an array of applications, particularly in medical imaging involving breast cancer diagnosis, laryngeal pathology diagnosis, and brain MR segmentation.

Edited by two leading researchers and with contributions from some of the best in the field, this volume fully reflects the diversity and richness of rough fuzzy image analysis. It deftly examines the underlying set theories as well as the diverse methods and applications.

About the Author

Sankar K. Pal is the director and a distinguished scientist of the Indian Statistical Institute in Kolkata.

James F. Peters is a professor in the Department of Electrical and Computer Engineering and group leader of the Computational Intelligence Laboratory at the University of Manitoba in Winnipeg, Canada.