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
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)