空间一致性约束谱聚类算法用于图像分割
Received:January 06, 2009  Revised:August 22, 2009  点此下载全文
引用本文:贾建华,焦李成.空间一致性约束谱聚类算法用于图像分割[J].Journal of Infrared and Millimeter Waves,2010,29(1):69~74
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Author NameAffiliationE-mail
JIA Jian-Hua Xidian University jjh163yx@163.com 
JIAO Li-Cheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Institute. of Intelligent Information Processing, Xidian University lcjiao@mail.xidian.edu.cn 
基金项目:国家高技术研究发展计划(863计划),国家自然科学基金项目(面上项目,重点项目,重大项目),国家重点基础研究发展计划(973计划),创新研究群体科学基金
中文摘要:近来出现的谱聚类算法在模式识别和图像分割中得到了广泛应用.与传统的聚类算法相比,谱聚类算法能在任意形状的样本空间上聚类且收敛于全局最优解.本研究从谱聚类和权核K-均值的等价性出发,基于图像的空间一致特性,提出了一种基于空间约束特性的谱聚类算法.该算法通过对加权核K-均值的目标函数加上空间一致约束项,利用近似逼近将目标函数最小化与谱聚类算法等价起来.仿真实验表明,此算法在图像分割中取得了比原始谱聚类算法更好的分割效果.
中文关键词:谱聚类  权核K-均值  空间一致特性  图像分割  
 
IMAGE SEGMENTATION BY SPECTRAL CLUSTERING ALGORITHM WITH SPATIAL COHERENCE CONSTRAINTS
Abstract: Image segmentation is one of the difficult problems in computer vision research. Recently spectral clustering has a wide application in pattern recognition and image segmentation. Compared with traditional clustering methods, it can cluster samples in any form feature space and has a global optimal solution. Originating from the equivalence between the spectral clustering and weighted kernel K-means, the authors proposed a spectral clustering algorithm with spatial constraints based on the spatially coherent property of images, also named continuous property. The spatially coherent property means that pixels in the neighbor region should share the same label assignment with the centre one with a high probability. The algorithm adds a term of spatial constraints to the objective function of weighted kernel K-means and makes the minimization of the objective function be equivalent to the spectral clustering through approximation. Experimental results show that our proposed algorithm outperforms the traditional spectral clustering in image segmentation.
keywords:spectral clustering  weighted kernel K-means  spatial coherence property  image segmentation  
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