[1]李扬,陆璐,崔红霞. 谱聚类图像分割中相似度矩阵构造研究[J].计算机技术与发展,2016,26(07):55-58.
　LI Yang,LU Lu,CUI Hong-xia. Research on Similarity Matrix Structure in Spectral Clustering Image Segmentation[J].,2016,26(07):55-58.
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 谱聚类图像分割中相似度矩阵构造研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年07期
页码:
55-58
栏目:
智能、算法、系统工程
出版日期:
2016-07-10

文章信息/Info

Title:
 Research on Similarity Matrix Structure in Spectral Clustering Image Segmentation
文章编号:
1673-629X（2016)07-0055-04
作者:
 李扬; 陆璐; 崔红霞
 渤海大学 信息科学与技术学院
Author(s):
 LI Yang; LU Lu; CUI Hong-xia
关键词:
 ; 图像分割; 谱聚类; 相似度矩阵; 颜色空间; 距离公式
Keywords:
 ; image segmentation; spectral clustering; similarity matrix; color space; distance formula
分类号:
TP391
文献标志码:
A
摘要:
 近年来谱聚类算法广泛应用于图像分割领域，而相似度矩阵的构造是谱聚类算法的关键。通常传统的谱聚类算法分割彩色图像时，仅采用一种颜色空间和距离计算公式构造相似度矩阵，而忽略了不同的颜色空间和距离计算公式构造的相似度矩阵对分割结果的影响，导致谱聚类算法有诸多的局限性。针对这个问题，文中分别采用RGB和HSV颜色空间，以及分别在两种颜色空间下使用欧氏距离、余弦距离和卡方距离公式，建立不同的相似度矩阵。分析比较不同构造方法的分割效果，得出了最优分割效果的相似度矩阵构造方法，提高了应用谱聚类算法分割彩色图像的有效性。通过计算性能评价指标查准率和查全率以及分割结果的准确率，验证了实验的可靠性和准确性。
Abstract:
 In recent years,spectral clustering algorithm is widely used in the field of image segmentation,and the structure of the similarity matrix is the key of it. When the color images are segmented by traditional spectral clustering algorithm,the only one of color space and distance calculation formula is usually used to construct similarity matrix. The influence of the segmentation results established on the dif-ferent color space and distance calculation formula is neglected,which leads to many limitations of spectral clustering algorithm. To solve this problem,using the formula of Euclidean distance,cosine distance and chi square distance,the different similarity matrices are estab-lished on RGB and HSV color space. The best segmentation construction method of the similarity matrix is obtained by analysis and com-parison of the effect of different construction methods. The effectiveness of spectral clustering algorithm for segmenting color images is improved. By calculating the accuracy of image segmentation results and the performance evaluation index of precision and recall,the reli-ability and accuracy of the experiment are verified.

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更新日期/Last Update: 2016-09-28