Histological image analysis by invariant descriptors

In this work we propose a comparative study between different descriptors in analysing histological images. In particular, our study is focused on measuring the accuracy of moments (Hu, Legendre, Zernike), Local Binary Patterns and co-occurrence matrices in classifying histological images. The experimentation has been conducted on well known public datasets: HistologyDS, Pap-smear, Lymphoma, Liver Aging Female, Liver Aging Male, Liver Gender AL and Liver Gender CR. The comparison results show that when combined with co-occurrence matrices and extracted from the RGB images, the orthogonal moments improve the classification performance considerably, imposing themselves as very powerful descriptors for histological image analysis.