Block-based ordinal co-occurrence matrices for texture similarity evaluation

In this paper we introduce a block-based approach for ordinal co-occurrence matrices aimed at improving robustness of the basic ordinal co-occurrence. Earlier, we have introduced two approaches for building ordinal co-occurrence matrices. One considers only the center pixel of a moving window as a seed point, compares it to its anti-causal neighbors and saves the occurrences of ordinal relations between pixels in the form of co-occurrence matrices. However, in that approach problems occur especially when considering textures with slightly varying gray levels in relatively large areas. The other method improves the robustness of the earlier method by considering also other pixels than the center pixel in the thresholded window as seed points. Main drawback of that method is the increased computational complexity. In order to avoid that, a block-based approach for building the ordinal co-occurrence matrices is introduced in this paper. Retrieval accuracy of the proposed method has shown to produce better results than existing techniques.