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LCD Defect Detection using Neural-network based on BEP  

Ko, Jung-Hwan (Department of Mechatronics, Inha Technical College)
Publication Information
전자공학회논문지 IE / v.48, no.2, 2011 , pp. 26-31 More about this Journal
Abstract
In this paper we show the LCD simulator for defect inspection using image processing algorithm and neural network. The defect inspection algorithm of the LCD consists of preprocessing, feature extraction and defect classification. Preprocess removes noise from LCD image, using morphology operator and neural network is used for the defect classification. Sample images with scratch, pinhole, and spot from real LCD color filter image are used. From some experiments results, the proposed algorithms show that defect detected and classified in the ratio of 92.3% and 94.5 respectively. Accordingly, in this paper, a possibility of practical implementation of the LCD defect inspection system is finally suggested.
Keywords
LCD; BEP; defect; neural network; thinning;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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