Extraction of Texture Features by Euclidean, Canberra & Both Distance

Ganesh Bhaiyya Regulwar

ISBN 10: 3843357404 / ISBN 13: 9783843357401

Published by LAP LAMBERT Academic Publishing Sep 2012, 2012

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -Texture describes the content of many real world images: for example, clouds, trees, bricks, hair, fabric etc. all of which have textural characteristics.Feature extraction is one of the most important tasks for efficient and accurate image retrieval purpose. In this book we are going to use Cosine-modulated wavelet transform based technique for extraction of texture features. The major advantages of Cosine-modulated wavelet transform are less implementation complexity, good filter quality, and ease in imposing the regularity conditions. Texture features are obtained by computing the energy, standard deviation and their combination on each subband of the decomposed image. To check the retrieval performance, texture database of 1856 textures is created from Brodatz album. Retrieval efficiency and accuracy using Cosine-modulated wavelet based features will be found to be superior to other existing methods. 104 pp. Englisch.

Seller Inventory # 9783843357401

Bibliographic Details

• Title: Extraction of Texture Features by Euclidean, Canberra & Both Distance
• Publisher: LAP LAMBERT Academic Publishing Sep 2012
• Publication Date: 2012
• Language: English
• ISBN 10: 3843357404
• ISBN 13: 9783843357401
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 7D millimeters 220 millimeters width by 150 millimeters height by 7 millimeters depth
• Weight: 173 grams

About this title

Synopsis

Texture describes the content of many real world images: for example, clouds, trees, bricks, hair, fabric etc. all of which have textural characteristics.Feature extraction is one of the most important tasks for efficient and accurate image retrieval purpose. In this book we are going to use Cosine-modulated wavelet transform based technique for extraction of texture features. The major advantages of Cosine-modulated wavelet transform are less implementation complexity, good filter quality, and ease in imposing the regularity conditions. Texture features are obtained by computing the energy, standard deviation and their combination on each subband of the decomposed image. To check the retrieval performance, texture database of 1856 textures is created from Brodatz album. Retrieval efficiency and accuracy using Cosine-modulated wavelet based features will be found to be superior to other existing methods.

About the Author

Master of Engineering in Information Technology.He is Working as an Assistant Professor in Engineering & Technology Institute at Maharashtra,INDIA.Area of research interest includes image processing,Software Engineering,Software Testing, Software Refactoring.He is life member of IACSIT and IAENG.He has published 21 papers in Journals & Conferences.