21 July 2017 Adaptive filtering based on LAB transform for FCM color image segmentation
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Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 1042025 (2017) https://doi.org/10.1117/12.2282075
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China
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.
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Ning Li, Ning Li, Shucheng Xu, Shucheng Xu, Zhongliang Deng, Zhongliang Deng, } "Adaptive filtering based on LAB transform for FCM color image segmentation", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042025 (21 July 2017); doi: 10.1117/12.2282075; https://doi.org/10.1117/12.2282075
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