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

Paul Southam; Richard W. Harvey

doi:10.1117/1.3258441

1 October 2009 Texture classification via morphological scale-space: Tex-Mex features

Paul Southam, Richard W. Harvey

Author Affiliations +

Journal of Electronic Imaging, Vol. 18, Issue 4, 043007 (October 2009). https://doi.org/10.1117/1.3258441

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.

©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Paul Southam and Richard W. Harvey "Texture classification via morphological scale-space: Tex-Mex features," Journal of Electronic Imaging 18(4), 043007 (1 October 2009). https://doi.org/10.1117/1.3258441

Published: 1 October 2009

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