Abstract: This paper introduce a method of region-based color image segmentation. The method firstly extracts color, texture and location features for each pixel; Secondly we make use of a model of mixture K Gaussians, the EM algorithm is applied to learning the parameters for a mixture of Gaussians, we choose the best suitable value of K through the rules we have proposed; Thirdly, those pixels that have similar features will be regarded a group; Finally, for each group we segment pixels again according to their positions and we can get segmentation regions of the image. Experiment shows this method has better segmentation performance.

摘要： 这篇文章介绍了一种基于区域的彩色图像分割方法。该方法首先提取图像像素点的颜色、纹理等特征；然后采用Gaussian混合模型，通过EM算法学习，根据提出的选择最佳高斯混合模型参数 的准则，确定 ；利用图像像素点特征的相似度在特征空间中粗略的将像素点划分为不同的组；最后在各个组内依据其位置信息对图像再进一步划分，得到图像的区域分割。实验结果表明，该分割方法具有较好的分割性能。