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Journal of Electronic Imaging

Texture classification via morphological scale-space: Tex-Mex features
Author(s): Paul Southam; Richard W. Harvey
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Paper Abstract

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.

Paper Details

Date Published: 1 October 2009
PDF: 16 pages
J. Electron. Imag. 18(4) 043007 doi: 10.1117/1.3258441
Published in: Journal of Electronic Imaging Volume 18, Issue 4
Show Author Affiliations
Paul Southam, Univ. of East Anglia Norwich (United Kingdom)
Richard W. Harvey, Univ. of East Anglia Norwich (United Kingdom)

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