Color texture representation using circular-processing based Hue-LBP for histo-pathology image analysis

Texture is considered one of most significant information sources in histo-pathology image analysis. To take advantage of information on color texture in digital histo-pathology, this work analyzes inherent characteristics of the hue component in the cylindrical color space, and introduces an effective color texture descriptor based on the LBP paradigm. Unlike existing LBP variants designed for linear data, the proposed descriptor, namely Hue-LBP, addresses the angular and periodic nature of hue and shows that color variation in the hue channel can be quantified by an angular variable in the range of [0,180]. By introducing the concept of color similarity as a metric to measure color variation, we obtain a histogram to describe local color texture patterns. Experimentation on histo-pathology image classification suggests that the proposed Hue-LBP is discriminative as it is capable of describing texture information conveyed by the hue components.