Image segmentation based on improved Ant-Tree algorithm
基于Ant-Tree聚类算法的图像分割

Image segmentation can be seen as the process of clustering the pixels with different characteristics. Considering the gray value, gratitude and neighborhood of the pixels synthetically, the Ant-Tree algorithm was introduced into image segmentation. As the resulting tree of Ant-Tree algorithm contains redundant information, an improved tree model was proposed in this paper. Besides, in order to optimize the process of clustering, a new initialization method was presented, and the method of K-means was also employed to modify the clustering center dynamically. Experiments and comparisons show that the Ant-Tree based clustering algorithm is an effective and efficient approach in image segmentation.