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Texture classification via morphological scale-space: Tex-Mex features

[+] Author Affiliations
Paul Southam

University of East Anglia, School of Computing Sciences, Norwich, NR4 7TJ, United Kingdom

Richard Harvey

University of East Anglia, School of Computing Sciences, Norwich, NR4 7TJ, United Kingdom

J. Electron. Imaging. 18(4), 043007 (November 20, 2009). doi:10.1117/1.3258441
History: Received March 30, 2009; Revised August 28, 2009; Accepted September 28, 2009; Published November 20, 2009; Online November 20, 2009
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We consider the problem of classifying textures. First, we consider images where the orientation of the texture is known. Then, we consider the classification of textures where the orientation is unknown. Last, classification in real scenes is considered. A wide variety of techniques are tested using the Outex framework. We introduce a new grayscale multiscale texture classification method based on a class of morphological filters called sieves. The method, denoted Tex-Mex because it extracts TEXture features using Morphological EXtrema filters, is shown to be among the best performing texture feature extraction methods. Tex-Mex features can be computed rapidly and are shown to be more robust and compact than the alternatives. Furthermore, they may be applied over windows of arbitrary size and orientation, a useful attribute when classifying texture in real scenes.

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© 2009 SPIE and IS&T

Citation

Paul Southam and Richard Harvey
"Texture classification via morphological scale-space: Tex-Mex features", J. Electron. Imaging. 18(4), 043007 (November 20, 2009). ; http://dx.doi.org/10.1117/1.3258441


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