基于Ncut的自适应图像分割方法
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Adaptive Image Segmentation Method Based on Ncut
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    摘要:

    为了解决传统归一化割(Normalized cut,Ncut)算法需要人工干预因素过多,限制了算法的通用性,本文对传统Ncut算法进行了改进,提出了自适应的图像分割方法。首先采用基团势的理论替代了传统的Ncut算法中计算权值矩阵时两个控制参数对结果的影响;然后为了减少K-means算法对分类数目和类中心的敏感,本文采用基于最小生成树的聚类方法对Ncut计算出的特征向量进行分类,得到最终的分类数目和初始类中心,然后再采用K-means算法进行聚类得到最终的分割结果。实验结果显示,本文的算法不仅提高了算法的通用性,并且分割效果比较好。

    Abstract:

    In order to solve the problem that requires some factors by manual in the traditional Ncut algorithm, limit the generality of the algorithm, an adaptive image segmentation method is proposed by improving the traditional Ncut algorithm. First, instead of the two control parameters on the calculation of weight matrix that influence the segmentation results in the traditional Ncut algorithm by groups of potential theory; then in order to reduce the sensitive to the number of the cluster and the center of the cluster in the K-means algorithm, calculate on the eigenvector of the Ncut algorithm by the minimum spanning tree, to get the final number of cluster and the center, and then uses the K-means clustering algorithm to get the final segmentation result. The experimental results show that the proposed method not only improves the versatility of the algorithm, and the segmentation is good.

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黄仁,冯阿瑞.基于Ncut的自适应图像分割方法[J].土木与环境工程学报(中英文),2013,35(Z2):107-110. Huang Ren, Feng Arui. Adaptive Image Segmentation Method Based on Ncut[J]. JOURNAL OF CIVIL AND ENVIRONMENTAL ENGINEERING,2013,35(Z2):107-110.[doi]

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  • 在线发布日期: 2014-02-25
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