In view of characteristics for coke optical texture in micrograph

a segmentation algorithm，combining mean shift and edge confidence

is proposed. Firstly

the edge confidence of image pixels is calculated. With the edge confidence

the weighting function of mean shift algorithm is computed. The sampling points of feature space are weighted in order to improve the accuracy of detected modes. Secondly

coke optical texture is segmented preliminarily by iterating the weighted mean shift vector. Because that the number of clusters in initial segmentation is larger than that of the actual clusters

which may result in over-segmentation

combining conditions are set by the spatial distance and the average value of the edge confidence

which are used to combine regions of homogenous texture. The coke optical texture is finally segmented with the new combining conditions. Experimental results show that with the proposed algorithm the segmentation among different optical textures of coke is reasonable and effective

which offers a reliable foundation for the recognition of coke optical texture.