基于二叉树结构聚类算法的彩色图像分割研究

C-Means Clustering Algorithm Based on Binary Tree Structure for Color Image Segmentation Research

提出了一种基于二叉树结构的彩色图像分割方法,首先对待分割图像采用最优阈值化方法获取R,G,B3个颜色空间的最佳阈值,然后通过构造自适用二叉树进行一次粗分割提取目标区域,最后采用C-均值聚类算法对二叉树的每个叶子节点进行精确分割.试验表明,该算法可以在保留原图像中大部分的信息的基础上,对目标物体进行有效的分割.

An effective segmentation method based on binary tree is proposed in this paper. First, this method uses the optimal threshold to get the best threshold in the R, G,B color space. Then a rough extract of the color image is gotten by constructing the self-adapting binary tree. After extracting, Cmeans clustering algorithm is used to improve the accuracy of the segmentation of the binary tree leaves. Experiment results show that this new method can be implemented efficiently. It can obtain high segmentation accuracy and reserve mass information of the original color image at the same time.