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- W2393610157 abstract "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." @default.
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- W2393610157 date "2010-01-01" @default.
- W2393610157 modified "2023-09-23" @default.
- W2393610157 title "Coke micrograph segmentation based on mean shift and edge confidence" @default.
- W2393610157 hasPublicationYear "2010" @default.
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