Color texture analysis based on fractal descriptors

Color texture classification is an important step in image segmentation and recognition. The color information is especially important in textures of natural scenes, such as leaves surfaces, terrains models, etc. In this paper, we propose a novel approach based on the fractal dimension for color texture analysis. The proposed approach investigates the complexity in R, G and B color channels to characterize a texture sample. We also propose to study all channels in combination, taking into consideration the correlations between them. Both these approaches use the volumetric version of the Bouligand–Minkowski Fractal Dimension method. The results show a advantage of the proposed method over other color texture analysis methods. ► We propose two fractal dimension-based approaches to characterize a color texture. ► The first approach investigates the complexity in R, G and B color channels. ► The second one investigates the complexity in the interaction among these three color channels. ► To achieve this, a new fractal descriptor is also proposed.