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http://dx.doi.org/10.13067/JKIECS.2012.7.5.1033

An Effective Steel Plate Detection Using Eigenvalue Analysis  

Park, Sang-Hyun (순천대학교 컴퓨터공학과)
Publication Information
The Journal of the Korea institute of electronic communication sciences / v.7, no.5, 2012 , pp. 1033-1039 More about this Journal
Abstract
In this paper, a simple and robust algorithm is proposed for detecting each steel plate from a image which contains several steel plates. Steel plate is characterized by line edge, so line detection is a fundamental task for analyzing and understanding of steel plate images. To detect the line edge, the proposed algorithm uses the small eigenvalue analysis. The proposed approach scans an input edge image from the top left corner to the bottom right corner with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Using the detected line edges, each plate is determined based on the directional information and the distance information of the line edges. The results of the experiments emphasize that the proposed algorithm detects each steel plate from a image effectively.
Keywords
Steel plate detection; Pattern recognition; Line detection; Edge clustering;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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