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Robust Image Segmentation Algorithm Based on Rough Sets and Fuzzy C-Means

机译:基于粗糙集和模糊C均值的鲁棒图像分割算法

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Image segmentation with the traditional Fuzzy C-means (FCM) algorithm only uses each pixel's gray value, when the image is corrupted by noises, the accuracy of segmentation will be greatly reduced. So, this paper proposed an image segmentation method which based on rough sets theory and fuzzy c-mean clustering. The test result shows that the method has a good segmentation performance.
机译:使用传统模糊C-Means(FCM)算法的图像分割仅使用每个像素的灰度值,当图像被噪声损坏时,分割的准确性将大大降低。因此,本文提出了一种基于粗糙集理论和模糊C均值聚类的图像分割方法。测试结果表明该方法具有良好的分割性能。

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