Fuzzy C-Mean Clustering Image Segmentation Algorithm Research for Sport Graphics Based on Artificial Life

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In this paper, linking with the basic principle of FCM (Fuzzy c-means clustering) algorithm, on the basis of theory research, a method of the cluster analysis of FCM based on artificial life is proposed. The artificial life approach is promising in image processing because it is inherently parallel and coincides with the self-governing biological process. Firstly, the approximate optimal solution obtained by the FCM algorithm is taken as the original value, then combined with intensity-texture-position feature space in order to produce connected regions shown in the image, the final segmentation result is achieved at last. The experiment results prove that in the view of the sport image segmentation, this algorithm provides fast segmentation with high perceptual segmentation quality.

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Periodical:

Edited by:

Jun Zhang, Zhijian Wang, Shuren Zhu and Xiaoming Meng

Pages:

2207-2210

DOI:

10.4028/www.scientific.net/AMM.263-266.2207

Citation:

X. Liu and L. Shi, "Fuzzy C-Mean Clustering Image Segmentation Algorithm Research for Sport Graphics Based on Artificial Life", Applied Mechanics and Materials, Vols. 263-266, pp. 2207-2210, 2013

Online since:

December 2012

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$38.00

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