Rotation invariant texture classification using Support Vector Machines
Yassine Ben Salem, Salem Nasri · 2011
In this paper, we study the problem of rotation invariant texture classifications. There are several methods in texture recognition problem, we compare three best known methods such us: Gabor wavelet filter, Local Binary Pattern operators (LBP) and co-occurrence matrix (GLCM). A multi-class Support Vector Machines (SVM) is used as a classifier. The three methods are evaluated based on two different databases: Brodatz and Outex to bring out a comparative study about the discrimination capabilities of those different families of texture classification methods. The experimental results show that some of the studied methods are more compatible with this classification problem than the others. The SVM classifier approve the running time of the algorithm of classification.