An Improved Image Segmentation Algorithm Based on KFCM-clustering
Author(s): WANG Yan, YANG Ge-lan, HE Jian-xin, School of Environmental Science and Engineering, Hunan City University, School of Software, Central South University
Pages: 1857-1860
Year: 2016 Issue: 11
Journal: Control Engineering of China
Keyword: Image segmentation; wavelet transform; clustering; speed;
Abstract: Traditional image segmentation methods often have some disadvantages, such as the over segmentation, the lower segmentation speed etc. In order to solve the above problems, a new region-based color image segmentation method is proposed in the paper, which transforms an image to L*a*b* space, and divides the image into sub-blocks, and extracts the color, texture and location features for every sub-block with combining the harr wavelet transform firstly. Then, the class number and the initial clustering centers are produced by using an improved Mean-shift algorithm. Finally, the method adopts an improved KFCM algorithm to achieve image segmentation. The experiment results show that this new algorithm can segment the color image into regions, and the segmentation result is good.
Pages: 1857-1860
Year: 2016 Issue: 11
Journal: Control Engineering of China
Keyword: Image segmentation; wavelet transform; clustering; speed;
Abstract: Traditional image segmentation methods often have some disadvantages, such as the over segmentation, the lower segmentation speed etc. In order to solve the above problems, a new region-based color image segmentation method is proposed in the paper, which transforms an image to L*a*b* space, and divides the image into sub-blocks, and extracts the color, texture and location features for every sub-block with combining the harr wavelet transform firstly. Then, the class number and the initial clustering centers are produced by using an improved Mean-shift algorithm. Finally, the method adopts an improved KFCM algorithm to achieve image segmentation. The experiment results show that this new algorithm can segment the color image into regions, and the segmentation result is good.
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