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利用高斯混合体模型和EM算法分割彩色图像 被引量:1

Segmentation of Color Images via Gaussian Mixer Model and EM Algorithm
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摘要 彩色图像分割是目前图像处理和模式识别中的一个重要研究领域。彩色图像可认为是由许多不同高斯随机变量共同作用而形成的,即利用高斯混合体模型可以描述彩色图像。图像中不同的部分对应数学模型中的不同高斯随机变量。因此,利用期望最大(EM)算法来求解随机变量的特征值,并用其对图像上的点进行分类,就可在一定程度上解决彩色图像分割的问题。 The segmentation of color images is an important research field of image processing and pattern recognition. A color image could be considered as the result from Gausslan mixer model to which several Gaussian random variables contribute. EM (Expected Maximum) algorithm can calculate the parameters of these Gaussian distribution. Therefore,the color image will be divided into several parts by the results.
作者 燕志征
机构地区 郑州大学
出处 《现代电子技术》 2005年第20期103-104,107,共3页 Modern Electronics Technique
关键词 高斯混合体 EM算法 图像分割 随机变量 Gaussian mixer model EM algorithm image segmentation random variable
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