A Taxonomy for Texture Description and Identification

A Taxonomy for Texture Description and Identi ...
A. Ravishankar Rao, A. Ravisha ...
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Last edited by ImportBot
January 31, 2024 | History

A Taxonomy for Texture Description and Identification

A central issue in computer vision is the problem of signal to symbol transformation. In the case of texture, which is an important visual cue, this problem has hitherto received very little attention. This book presents a solution to the signal to symbol transformation problem for texture. The symbolic de- scription scheme consists of a novel taxonomy for textures, and is based on appropriate mathematical models for different kinds of texture. The taxonomy classifies textures into the broad classes of disordered, strongly ordered, weakly ordered and compositional. Disordered textures are described by statistical mea- sures, strongly ordered textures by the placement of primitives, and weakly ordered textures by an orientation field. Compositional textures are created from these three classes of texture by using certain rules of composition. The unifying theme of this book is to provide standardized symbolic descriptions that serve as a descriptive vocabulary for textures. The algorithms developed in the book have been applied to a wide variety of textured images arising in semiconductor wafer inspection, flow visualization and lumber processing. The taxonomy for texture can serve as a scheme for the identification and description of surface flaws and defects occurring in a wide range of practical applications.

Publish Date
Pages
224

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Previews available in: English

Edition Availability
Cover of: A Taxonomy for Texture Description and Identification
A Taxonomy for Texture Description and Identification
Oct 18, 1990, Springer My Copy UK
paperback
Cover of: A Taxonomy for Texture Description and Identification
A Taxonomy for Texture Description and Identification
1990, Springer US
electronic resource / in English

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Book Details


The Physical Object

Format
paperback
Number of pages
224

ID Numbers

Open Library
OL28137854M
ISBN 10
1461397782
ISBN 13
9781461397786

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January 31, 2024 Edited by ImportBot import existing book
May 25, 2020 Created by ImportBot Imported from amazon.com record