JCP 2014 Vol.9(7): 1678-1683 ISSN: 1796-203X
doi: 10.4304/jcp.9.7.1678-1683
doi: 10.4304/jcp.9.7.1678-1683
Image Segmentation with Fuzzy Clustering Based on Generalized Entropy
Kai Li, Zhixin Guo
School of Mathematics and Computer Science, Hebei University, Baoding, China
Abstract—Aimed at fuzzy clustering based on the generalized entropy, an image segmentation algorithm by joining space information of image is presented in this paper. For solving the optimization problem with generalized entropy’s fuzzy clustering, both Hopfield neural network and multi-synapse neural network are used in order to obtain cluster centers and fuzzy membership degrees. In addition, to improve anti-noise characteristic of algorithm, a window is introduced. In experiments, some commonly used images are selected to verify performance of algorithm presented. Experimental results show that the image segmentation of fuzzy clustering based on generalized entropy using neural network performs better compared to FCM and BCFCM_S1.
Index Terms—image segmentation, spatial information, generalized entropy, neural network
Abstract—Aimed at fuzzy clustering based on the generalized entropy, an image segmentation algorithm by joining space information of image is presented in this paper. For solving the optimization problem with generalized entropy’s fuzzy clustering, both Hopfield neural network and multi-synapse neural network are used in order to obtain cluster centers and fuzzy membership degrees. In addition, to improve anti-noise characteristic of algorithm, a window is introduced. In experiments, some commonly used images are selected to verify performance of algorithm presented. Experimental results show that the image segmentation of fuzzy clustering based on generalized entropy using neural network performs better compared to FCM and BCFCM_S1.
Index Terms—image segmentation, spatial information, generalized entropy, neural network
Cite: Kai Li, Zhixin Guo, "Image Segmentation with Fuzzy Clustering Based on Generalized Entropy," Journal of Computers vol. 9, no. 7, pp. 1678-1683, 2014.
General Information
ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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