李丹丹, 史秀璋. 基于HSI空间和K-means方法的彩色图像分割算法[J]. 微电子学与计算机, 2010, 27(7): 121-124.
引用本文: 李丹丹, 史秀璋. 基于HSI空间和K-means方法的彩色图像分割算法[J]. 微电子学与计算机, 2010, 27(7): 121-124.
LI Dan-dan, SHI Xiu-zhang. A Kind of Color Image Segmentation Algorithm Based on HSI Space and K-means Method[J]. Microelectronics & Computer, 2010, 27(7): 121-124.
Citation: LI Dan-dan, SHI Xiu-zhang. A Kind of Color Image Segmentation Algorithm Based on HSI Space and K-means Method[J]. Microelectronics & Computer, 2010, 27(7): 121-124.

基于HSI空间和K-means方法的彩色图像分割算法

A Kind of Color Image Segmentation Algorithm Based on HSI Space and K-means Method

  • 摘要: 提出了一种新的彩色图像聚类分割算法,选用HSI空间作为彩色分割空间,在研究H分量的聚类算法中,该分量的圆循环特性被充分的考虑,同时也定义了H分量空间中两点距离的定义和中心的概念;选用最重要的H分量和I分量作为分割聚类特征,运用模糊隶属度刻画了该聚类特征,最后运用K-means算法对彩色图像进行聚类分割.实验结果表明,此算法能够准确地从彩色图像中提取目标区域,且在H分量和I分量上联合分割的结果好于在单个分量上分割的结果.

     

    Abstract: A kind of clustering algorithm for color image segmentation is proposed, choosing HSI representation as the color segmentation space, in the study of H component, the circulation characteristics were full consideration, also the distance of two points and centers of H component is defined. Choosing the most important component of H and I component as segmentation clustering features, using fuzzy membership function depicts the clustering features, at last K-means clustering algorithm is used to segment color image. An experiments is given on bone regional segmentation, and achieve good segmentation results, experimental results shows that the results of the H and I components is superior to the results on a single component of HIS space.

     

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