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http://dx.doi.org/10.5392/JKCA.2011.11.3.018

Inspection of Coin Surface Defects using Multiple Eigen Spaces  

Kim, Jae-Min (홍익대학교 전자전기공학부)
Ryoo, Ho-Jin (홍익대학교 전자전기공학부)
Publication Information
The Journal of the Korea Contents Association / v.11, no.3, 2011 , pp. 18-25 More about this Journal
Abstract
In a manufacturing process of metal coins, surface defects of coins are manually detected. This paper describes an new method for detecting surface defects of metal coins on a moving conveyor belt using image processing. This method consists of multiple procedures: segmentation of a coin from the background, alignment of the coin to the model, projection of the aligned coin to the best eigen image space, and detection of defects by comparison of the projection error with an adaptive threshold. In these procedures, the alignement and the projection are newly developed in this paper for the detection of coin surface defects. For alignment, we use the histogram of the segmented coin, which converts two-dimensional image alignment to one-dimensional alignment. The projection reduces the intensity variation of the coin image caused by illumination and coin rotation change. For projection, we build multiple eigen image spaces and choose the best eigen space using estimated coin direction. Since each eigen space consists of a small number of eigen image vectors, we can implement the projection in real- time.
Keywords
Defected Surface Inspection; Diffused Reflection Noise; Pattern Alignment; Adaptive Eigen Image;
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