Illumination Invariant Color Texture Analysis Based on Sum- and Difference-Histograms

Color texture algorithms have been under investigation for quite a few years now. However, the results of these algorithms are still under considerable influence of the illumination conditions under which the images were captured. It is strongly desireable to reduce the influence of illumination as much as possible to obtain stable and satisfying classification results even under difficult imaging conditions, as they can occur e.g. in medical applications like endoscopy. In this paper we present the analysis of a well-known texture analysis algorithm, namely the sum- and difference-histogram features, with respect to illumination changes. Based on this analysis, we propose a novel set of features factoring out the illumination influence from the majority of the original features. We conclude our paper with a quantitative, experimental evaluation on artificial and real image samples.

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