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Proceedings Paper

Adaptive filtering based on LAB transform for FCM color image segmentation
Author(s): Ning Li; Shucheng Xu; Zhongliang Deng
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Paper Abstract

In this paper, we propose an adaptive mean filter FCM algorithm based on LAB transform to improve the anti-noise ability of the traditional FCM in image segmentation, which lack of using spatial information. The algorithm firstly counts the peak value of the whole image pixel, and then weights the transformed color component according to the statistical result, and gives the different color space different information amount. At the same time, the algorithm combines the variance of the image to filter the image, and adjusts the filter degree adaptively to use the spatial information most effectively. The experimental results show that our algorithm is better than the traditional algorithm in segmentation effect, and has great improvement in anti-noise ability.

Paper Details

Date Published: 21 July 2017
PDF: 6 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042025 (21 July 2017); doi: 10.1117/12.2282075
Show Author Affiliations
Ning Li, Beijing Univ. of Posts and Telecommunications (China)
Shucheng Xu, Beijing Univ. of Posts and Telecommunications (China)
Zhongliang Deng, Beijing Univ. of Posts and Telecommunications (China)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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