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    基于改进的K-means聚类图像分割算法

    Image Segmentation Based on a Modified K-means Algorithm

    • 摘要: 介绍一种采用K-L变换、二维向量小波和改进的K-means结合的图像分割算法。阐述和分析了二维向量小波变换和Laws纹理能量测度,得出图像每个像素点可用9个纹理特性来描述的结论。运用K-means算法的思想对其进行改进,最后得出分割后的图像。试验结果证明,运用以上处理方法可显著提高分割速度和精度。

       

      Abstract: An image segmentation method combined K-L transformation, two dimensional multi-wavelet and modified K-means algorithm was introduced. Two dimensional multi-wavelet and laws texture measurement were analyzed. A conclusion was got that every pixel had nine texture measure for describing image. A modified K-means algorithm applied the thought of K-means was proposed, and the target image was acquired. The experiment results proved that the FKM method was usefull because of its accuracy and computing velocity.

       

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