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融合快速全局K-means与区域合并的图像分割
引用本文:王虹,覃刘波.融合快速全局K-means与区域合并的图像分割[J].计算机工程与应用,2012,48(7):187-190,223.
作者姓名:王虹  覃刘波
作者单位:武汉理工大学信息工程学院,武汉,430063
摘    要:提出一种融合快速全局K-means与区域合并的图像分割方法。该方法利用中值滤波方法对图像去噪;运用快速全局K-means算法对图像的颜色空间进行聚类分析;结合区域合并准则,对初始分割合并得到最终的分割结果。实验表明,与同类算法比较,该方法的分割结果在图像细节方面能够很好地满足人的主观视觉。

关 键 词:图像分割  快速全局K-means  区域合并  聚类分析

Method ofimage segmentation based on fast global K-means algorithm and region merging
WANG Hong , QIN Liubo.Method ofimage segmentation based on fast global K-means algorithm and region merging[J].Computer Engineering and Applications,2012,48(7):187-190,223.
Authors:WANG Hong  QIN Liubo
Affiliation:Institute of Information Technology, Wuhan University of Technology, Wuhan 430063, China
Abstract:In this paper, a method ofimage segmentation is presented, which based on fast global K-means and region merging. Medial filter is used to remove the noise of target image. The initial segmented result is obtained by using fast global K-means clustering algorithm in the color space. A region merging strategy is used to merge the initial regions with the goal of forming the final segmentation result. The simulation results indicate that compared with other methods, the segmentation result is well consistent with human perception, especially in image details.
Keywords:image segmentation  fast global K-means algorithm  region merging  clustering analysis
本文献已被 CNKI 维普 万方数据 等数据库收录!
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