基于核函数及空间邻域信息的FCM图像分割新算法

针对传统FCM算法在进行图像分割时对噪声敏感的问题,提出一种新的基于核函数及空间邻域信息的FCM图像分割算法。该算法根据像素间灰度值的差异程度,将空间信息引入传统的FCM算法,建立新的包含邻域信息的隶属度迭代函数,实现图像的分割。同时,算法还引入核函数,用内核诱导距离代替了传统FCM算法中的欧式距离,对输入图像的样本特征进行优化。实验结果表明,本文算法能够获得较好的分割效果,同时具有较强的抑制噪声的能力。

Modified kernel-based fuzzy c-means algorithm with spatial information for image segmentation

This paper proposes a Modified kernel-based FCM algorithm that incorporates the spatial information into the membership function for clustering(MSKFCM).In the algorithm,we replace the original Euclidean distance with a Gaussian kernel-induced distance,then use the distribution statistics of the neighborhood pixels and the weight coefficient based on the distance attributes to form a new membership function.Experimental results show that MSKFCM can segment images more effectively and provide more robust segmentation results.