Color image segmentation using Gaussian mixture model and EM algorithm

摘要：

The segmentation of color image is an important research field of image processing and pattern recognition.A color image could be considered as the result from Gaussian mixture model (GMM) to which several Gaussian random variables contribute.In this paper,an efficient method of image segmentation is proposed.The method uses Gaussian mixture models to model the original image,and transforms segmentation problem into the maximum likelihood parameter estimation by expectation-maximization (EM) algorithm.And using the method to classify their pixels of the image,the problem of color image segmentation can be resolved to some extent.The experiment results confirm this method validity.

关键词： Gaussian mixture model EM algorithm image segmentation random variable

作者: Fu Zhaoxia Wang Liming Han Yan

作者单位: Science and Technology on Electronic Test &Measurement Laboratory and Key Laboratory of Instrumentat Science and Technology on Electronic Test &Measurement Laboratory and Key Laboratory of Instrumentat

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 112-115

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）