Sum and Difference Histograms for Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Markov Random Field Models for Unsupervised Segmentation of Textured Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized Co-Occurrence Matrix for Multispectral Texture Analysis
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
A multiscale representation including opponent color features for texture recognition
IEEE Transactions on Image Processing
Perceptually uniform color spaces for color texture analysis: an empirical evaluation
IEEE Transactions on Image Processing
Illumination invariant color texture analysis based on sum- and difference-histograms
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
A multi-classifier approach to face image segmentation for travel documents
Expert Systems with Applications: An International Journal
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In this paper we present a new approach for color texture classification which extends the gray level sum- and difference histogram features [8]. Intra- and inter-plane second order features capture the spatial correlations between color bands. A powerful set of features is obtained by non-linear color space conversion to HSV and thresholding operation to eliminate the influence of sensor noise on color information. We present an evaluation of classification performance using four different image sets.