Image processing based on percolation model

Tomoyuki Yamaguchi*, Shuji Hashimoto

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    36 Citations (Scopus)


    This paper proposes a novel image processing method based on a percolation model. The percolation model is used to represent the natural phenomenon of the permeation of liquid. The percolation takes into account the connectivity among the neighborhoods. In the proposed method, a cluster formation by the percolation process is performed first. Then, feature extraction from the cluster is carried out. Therefore, this method is a type of scalable window processing for realizing a robust and flexible feature extraction. The effectiveness of proposed method was verified by experiments on crack detection, noise reduction, and edge detection.

    Original languageEnglish
    Pages (from-to)2044-2052
    Number of pages9
    JournalIEICE Transactions on Information and Systems
    Issue number7
    Publication statusPublished - 2006 Jul


    • Cluster formation
    • Feature extraction
    • Percolation
    • Scalable window

    ASJC Scopus subject areas

    • Information Systems
    • Computer Graphics and Computer-Aided Design
    • Software


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