In this paper, an innovative method to characterize texture images based on discrete
Tchebichef moments (DTM) is presented. A global signature pattern is derived from the
moment matrix by taking into account both the magnitude of the moments and their order.
The performance of our method for several texture classification problems was compared
with that achieved through other standard approaches. These include Haralick’s gray level
co-occurrence matrices (GLCM), Gabor filters (GF) and local binary patterns (LBP). An
extensive texture classification study was carried out by selecting images with different
contents from Brodatz, Outex and VisTex databases. The results show that the proposed
method is able to capture the essential information about texture showing comparable or
even higher performance than conventional procedures. Thus, it can be considered as an
effective and competitive technique for texture characterization.
