Fuzzy C-mean algorithm (FCM) has been well used in the field of color image segmentation. But it is sensitive to initial clustering center and membership matrix, and likely converges into the local minimum, which causes the quality of image segmentation lower. By use of the properties-ergodicity, randomicity of chaos, a new image segmentation algorithm is proposed, which combines the chaos particle swarm optimization (CPSO) and FCM clustering. Some experimental results are shown that this method not only has the ability to prevent the particles to convergence to local optimum, but also has faster convergence and higher accuracy for segmentation. Using the feature distance instead of Euclidian distance, robustness of this method is enhanced.
一种基于混合方法的彩色图像分割算法*----结合分水岭算法、种子区域生长和区域合并的混合方法A Color Image Segmentation Algorithm Based on Hybrid Method*—By Integrating Watershed with Automatic Seeded Region Growing and Merging