An efficient color image classification method using gradient magnitude based angle cooccurrence matrix
Rui Zhang, Baolin Yin, Qiyang Zhao, Bin Yang · 2010
In this paper, a novel texture feature GMACM, is presented according to the statistics of gradient angle cooccurrence in color images. Based on three different types of gradients defined in the RGB space, the corresponding GMACMs are introduced. With some well-designed color image classification experiments, it is shown that GMACMs outperform GLCM and Gabor filters significantly in efficiency and accuracy. It could be concluded that GMACM is powerful in classifying and understand color images.