Colour Contrast Occurrence matrix: a vector and perceptual texture feature

Overview & Synopsis

Texture discrimination was the second more important task studied after colour perception and characterization. Nevertheless, few works explore the colour extension of these works and none for vectorial processing of this important visual information. In this work we propose a novel and vector processing for colour texture characterization, the color contrast occurrence matrix C2O. This new texture feature is based on the colour dierence assessment. To be link to the human perception, the colour dierence is expressed using a perceptual distance expressed in CIELab and two angles characterizing the chromaticity and darker or lighter direction. Through this new attribute, we analyze the stability to changes in illumination, viewpoint and spectrum of the light source in front of dierent texture image databases . Thanks to our construction, we avoid the main limit of existing texture features requiring an initial colour quantization or a binarization inside the texture construction. Keeping the small local contrast, we obtain a more accurate texture feature description explaining the obtained results. Then we carry out the construction of a features vector by occurrence quantization, keeping the initial ideas of Julesz, Haralick and Ojala, for the classication purposes. The results show best correct classication percentages in databases that with important spatio-chromatic complexity as ALOT.