Image Processing Based on Percolation Model(Feature Extraction,<Special Section>Machine Vision Applications)

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概要

• 論文の詳細を見る

• 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.

• 社団法人電子情報通信学会の論文
• 2006-07-01

著者

• Yamaguchi Tomoyuki

  Dept. Of Applied Physics Waseda University

• Hashimoto Shuji

  Dept. Of Applied Physics Waseda University

• HASHIMOTO Shuji

  Dept. of Applied Physics, Waseda University

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• Image Processing Based on Percolation Model(Feature Extraction,Machine Vision Applications)

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