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Image Processing Based on Percolation Model Tomoyuki YAMAGUCHI Shuji HASHIMOTO Publication IEICE TRANSACTIONS on Information and Systems Vol.E89-D No.7 pp.2044-2052 Publication Date: 2006/07/01 Online ISSN: 1745-1361 DOI: 10.1093/ietisy/e89-d.7.2044 Print ISSN: 0916-8532 Type of Manuscript: Special Section PAPER (Special Section on Machine Vision Applications) Category: Feature Extraction Keyword: percolation, scalable window, cluster formation, feature extraction, Full Text: PDF(1.4MB)>>
Summary: 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. | ||||||||||
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