Computer Science ›› 2015, Vol. 42 ›› Issue (3): 307-310.doi: 10.11896/j.issn.1002-137X.2015.03.063

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Image Classification and Identification through SVM Based on Fuzzy Kernel Clustering

YU Wen-yong, KANG Xiao-dong, GE Wen-jie and WANG Hao   

  • Online:2018-11-14 Published:2018-11-14

Abstract: A method of image classification and identification combined with characteristic field and SVM based on fuzzy kernel clustering was proposed in this paper.First,the structure corresponds to image color of human visual characteristics and data field of texture.For one thing,the new threshold is introduced and the image texture is established.For another,attractive pixel to pixel area is weighted and processed,and the spatial distribution of color is described by using dispersion of color spatial distribution.Second,SVM based on fuzzy kernel clustering is adopted to study a classification of image identification.On the feature space,not only the relationship of samples between its cluster centers but also the each samples are all taken into account.The relation between each samples in the cluster is measured based on fuzzy connectedness and a binary tree classifier is constructed.Experimental results show that this method can achieve a better effect of image classification.

Key words: Support vector machine (SVM),Membership function,Fuzzy kernel clustering,Data field

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