【摘要】 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。更多还原

【Abstract】 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.更多还原