• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Tang Yang, Pan Zhigeng, Tang Min, Pheng Ann Heng, Xia Deshen. Image Segmentation with Hierarchical Mean Shift[J]. Journal of Computer Research and Development, 2009, 46(9): 1424-1431.
Citation: Tang Yang, Pan Zhigeng, Tang Min, Pheng Ann Heng, Xia Deshen. Image Segmentation with Hierarchical Mean Shift[J]. Journal of Computer Research and Development, 2009, 46(9): 1424-1431.

Image Segmentation with Hierarchical Mean Shift

More Information
  • Published Date: September 14, 2009
  • Connected channels were found somewhere in the feature space in traditional mean shift method. Consequently, to accomplish the segmentation by only one trial often leads to unsatisfactory result, especially in weak edges or regions without Gaussian character. To solve this problem, the authors design a hierarchical segment method based on mean shift technique. Upon on the original sampling data, clustering is performed iteratively with different bandwidths on the centers gained previously. Thus, a tree structure is established between the nodes in different levels. According to the inheritance relationship, the leaf nodes are merged and classified into different categories finally. The method was implemented and tested in both gray and color images. Compared with the traditional mean shift method, the hierarchical method has advantage to reserve the detaisl in the same scale. Also, although the multiple time clustering is needed, the computation cost will not increase obviously due to the decreasing sample sizes and varied bandwidths. The hierarchical mean shift method has been proved to be promising in the experiments. But more theoretical analysis is required and the method also needs to be improved by more experiments.
  • Related Articles

    [1]Duan Wenxue, Hu Ming, Zhou Qiong, Wu Tingming, Zhou Junlong, Liu Xiao, Wei Tongquan, Chen Mingsong. Reliability in Cloud Computing System: A Review[J]. Journal of Computer Research and Development, 2020, 57(1): 102-123. DOI: 10.7544/issn1000-1239.2020.20180675
    [2]Lou Jungang, Jiang Jianhui, Shen Zhangguo, Jiang Yunliang. Software Reliability Prediction Modeling with Relevance Vector Machine[J]. Journal of Computer Research and Development, 2013, 50(7): 1542-1550.
    [3]Wu Caihua, Liu Juntao, Peng Shirui, Li Haihong. Deriving Markov Chain Usage Model from UML Model[J]. Journal of Computer Research and Development, 2012, 49(8): 1811-1819.
    [4]Li Haifeng, Li Qiuying, and Lu Minyan. Software Reliability Modeling with Logistic Test Coverage Function[J]. Journal of Computer Research and Development, 2011, 48(2): 232-240.
    [5]Mu Fei, Xue Wei, Shu Jiwu, and Zheng Weimin. An Analytical Model for Large-Scale Storage System with Replicated Data[J]. Journal of Computer Research and Development, 2009, 46(5): 756-761.
    [6]Zhang Hongcan, Xue Wei, and Shu Jiwu. An Expandable Distributed RAID Storage Cluster System[J]. Journal of Computer Research and Development, 2008, 45(4): 741-746.
    [7]Ren Xiaoxi, Li Renfa, Jin Shengzhen, Zhang Kehuan, Wu Qiang. Research on Reliability of a Reconfigurable Data Processing System Based on JBits[J]. Journal of Computer Research and Development, 2007, 44(4): 722-728.
    [8]Zhou Xuehai, Yu Jie, Li Xi, and Wand Zhigang. Research on Reliability Evaluation of Cache Based on Instruction Behavior[J]. Journal of Computer Research and Development, 2007, 44(4): 553-559.
    [9]Zhao Jing, Liu Hongwei, Cui Gang, and Yang Xiaozong. A Software Reliability Growth Model Considering Testing Environment and Actual Operation Environment[J]. Journal of Computer Research and Development, 2006, 43(5): 881-887.
    [10]Zhao Jing, Liu Hongwei, Cui Gang, and Yang Xiaozong. A Software Reliability Growth Model Considering Differences Between Testing and Operation[J]. Journal of Computer Research and Development, 2006, 43(3): 503-508.

Catalog

    Article views (1031) PDF downloads (686) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return