Expanded order co-occurrence matrix to differentiate between coal and gangue based on interval grayscale compression
煤矸区分中的间隔灰度压缩扩阶共生矩阵

In order to play the role of co-occurrence matrix inertia in the analysis and retrieval of image texture efficiently,a new expanded order co-occurrence matrix inertia based on interval grayscale compression is studied. One part of the grayscale information of the original image is compressed and another is retained in this integrated approach. The uncompressed grayscale information is extracted by an order expansion of the matrix. The effects of the grayscale information are used randomly. Experimental results show that the algorithm differentiaties the target types better than the conventional co-occurrence matrix based algorithms.More than 82% of the objects are differentiated correctly, and the methods appropriate distinction threshold is easier to set and faster.