会议专题

Color image segmentation using Gaussian mixture model and EM algorithm

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.

Gaussian mixture model EM algorithm image segmentation random variable

Fu Zhaoxia Wang Liming Han Yan

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

国际会议

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)

太原

英文

112-115

2011-02-26(万方平台首次上网日期,不代表论文的发表时间)