Self-similarity and points of interest in textured images

Authors:
Shripad Kondra;Alfredo Petrosino
Affiliations:
Neuroimaging Lab, National Brain Research Centre, India;Department of Applied Science, University of Naples
Venue:
PerMIn'12 Proceedings of the First Indo-Japan conference on Perception and Machine Intelligence
Year:
2012

Citing 11
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Abstract

We propose the application of symmetry for texture classification. First we propose a feature vector based on the distribution of local bilateral symmetry in textured images. This feature is more effective in classifying a uniform texture versus a non-uniform texture. The feature when used with a texton-based feature improves the classification rate and is tested on 4 texture datasets. Secondly, we also present a global clustering of texture based on symmetry.