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Texture Classification Using Statistical and Soft-Computing Methods

Stolpmann, Alexander and Dooley, Laurence S. (2000). Texture Classification Using Statistical and Soft-Computing Methods. In: Pietikäinen, M. K. ed. Texture Analysis in Machine Vision. Machine Perception and Artificial Intelligence Series, 40 (1). USA: World Scientific Publishing, pp. 53–69.

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About the book: Texture analysis is an important generic research area of machine vision. The potential areas of application include biomedical image analysis, industrial inspection, analysis of satellite or aerial imagery, content-based retrieval from image databases, document analysis, biometric person authentication, scene analysis for robot navigation, texture synthesis for computer graphics and animation, and image coding. Texture analysis has been a topic of intensive research for over three decades, but the progress has been very slow.
A workshop on "Texture Analysis in Machine Vision" was held at the University of Oulu, Finland, in 1999, providing a forum for presenting recent research results and for discussing how to make progress in order to increase the usefulness of texture in practical applications. This book contains extended and revised versions of the papers presented at the workshop. The first part of the book deals with texture analysis methodology, while the second part covers various applications. The book gives a unique view of different approaches and applications of texture analysis.

Item Type: Book Section
ISBN: 981-02-4373-1, 978-981-02-4373-9
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 11718
Depositing User: Laurence Dooley
Date Deposited: 19 Sep 2008 08:50
Last Modified: 07 Dec 2018 09:12
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