以模糊C均值（FCM）聚类理论为基础，选用符合人眼视觉特性的HSI颜色空间，提出了一种新的多分量彩色图像分割算法。该算法首先结合数据分布特点确定出H分量与I分量的初始聚类中心；然后利用FCM聚类技术对H分量、I分量进行分类处理，以得到不同分量的像素点隶属度；最后，将所得到的不同分量像素点隶属度组织成2维特征，并以此进行模糊聚类图像分割。实验结果表明，该算法可有效提高图像分割效果，其分割结果优于传统FCM聚类图像分割方案。

We propose a FCM based image segmentation algorithm using multi color components. Firstly, the image is converted from RGB color space to HSI color space, and initial clustering centers of H component and I component are selected according to the data distribution. Then, the FCM algorithm is performed on the H component and I component, and we can obtain the image pixel membership for H component and I component. Finally, two dimensional image features are constructed with the image pixel membership, and the FCM based image segmentation is performed using two dimensional image features. Experimental results show that the proposed method is simple and work well for most images, and has better segmentation effect than the existing FCM color image segmentation.