计算机科学 ›› 2010, Vol. 37 ›› Issue (7): 264-266.

• 图形图像 • 上一篇    下一篇

基于多阶抽样谱图聚类彩色图像分割

朱峰,宋余庆,朱玉全,许莉莉,金洪伟   

  1. (江苏大学理学院 镇江212013)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金(60841003)资助。

Color Image Segmentation Based on Spectral Clustering Using Multi-sampling

ZHU Feng,SONG Yu-qing,ZHU Yu-quan,XU Li-li,JIN Hong-wei   

  • Online:2018-12-01 Published:2018-12-01

摘要: 针对谱聚类应用于图像分割时权矩阵的谱难以计算的实际问题,设计了一个图像多阶抽样谱图聚类算法。首先,给出了采样数定理及其证明,并推导出与聚类类别数和最小聚类数相关的最小采样数目;其次,根据最小采样数数目,对像素点进行均匀采样,并利用谱聚类对采样点进行聚类,设计一个罚函数,通过多次抽样,消除抽样对谱聚类模型稳定性的影响;最后,定义了像素点和类之间的距离,对剩余的点按距离最近原则进行聚类。实验结果表明了算法的有效性。

关键词: 谱聚类,多阶抽样,图像分割,归一化割

Abstract: Spectral clustering for image segmentation is difficult to calculate the spectrum of weighted matrix. A multistage sampling spectrum image clustering algorithm was designed to eliminate it. First, the sampling theorem was given and proved, and the minimum sample size was derived according to the smallest cluster and cluster number. Secondly,image pixels were sampled based on the minimum sample size and a penalty function was proposed by repeated sampling for the elimination of sampling model on the stability effects of spectral clustering. Finally, the distance between a pixel point and categories was definited, the remaining points were assigned respective cluster depending on the principles ofthe nearest distence. I}he experimental results show the effectiveness of the algorithm.

Key words: Spectral clustering,Multi sampling,Image segmentation,Normalized cut

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