吉林大学学报(工学版) ›› 2012, Vol. 42 ›› Issue (增刊1): 225-230.

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Fuzzy C-means clustering for color image segmentation based on S and V color components

SHEN Xuan-jing, HE Yue   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2012-03-26 Online:2012-09-01 Published:2012-09-01

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Abstract: In order to segment the color image quickly and efficiently, a color image segmentation algorithm based on HSV color space was proposed. Firstly the distribution of S and V color components in the color image was calculated, and then the statistics were clustered by using the fast fuzzy C-means clustering algorithm, finally the color image was segmented according to the target color number and the cluster centers obtained. Compared with the existing color image algorithms, the test results show that the proposed algorithm can accurately extract the target regions of different color images with less remaining background information, meanwhile the scale of the image has less impact on the computing speed, so has faster speed and better segment results can be achieved.

Key words: computer application, color image segmentation, fast fuzzy C-means algorithm, S and V color components

CLC Number: 

  • TP391
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