Modified integrative color intensity co-occurrence matrix for texture image representation

Gray-level co-occurrence matrix (GLCM) is one of the most used methods for texture representation. As it can be computed only from gray-level images, a significant amount of information that could be provided by color is totally ignored. We propose a generalization of GLCM from gray level to hue saturation value color space, which we refer to as modified integrative color intensity co-occurrence matrix (MICICM). To reach such a generalization, a mapping function, which determines for each pixel value the bin it falls into, is needed. In many previous studies, this function uses a hard mapping where all pixel values that fall in a bin are considered as the same, regardless of their values. This presents a number of drawbacks. To fix them, we introduce a color and gray-level mapping scheme based on a set of weight assignment functions we propose. In our scheme, each pixel is mapped to more than one possible color (and gray-level) bin, to avoid the drawbacks of hard mapping. Although a fuzzy-based scheme has been recently proposed, our MICICM has successfully outperformed it and those of the state of the art. Our findings make several noteworthy contributions to image representation. (C) 2016 SPIE and IS&T