Fast and accurate computation of orthogonal moments for texture analysis

In this work we propose a fast and stable algorithm for the computation of the orthogonal moments of an image. Indeed, the traditional orthogonal moments formulations are characterized by a high discriminative power, but also by a large computational complexity, which limits their real-time application. The recursive approach described in this paper aims to solve these limitations. In our experiments, we evaluate the effectiveness of the recursive formulations and its performance for the reconstruction task. The results show a great reduction in the computational complexity with respect to the closed form formulation, together with a greater accuracy in reconstruction. Then, in order to assess and compare the accuracy of the computed moments in texture analysis, we perform classification experiments on six well-known databases of texture images. Again, the recursive formulation performs better in classification than the closed form representation. More importantly, if computed from the GLCM of the image, the new moments outperform significantly some of the most diffused state-of-the-art descriptors for texture classification.