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http://dx.doi.org/10.5302/J.ICROS.2006.12.3.241

A PCB Character Recognition System Using Rotation-Invariant Features  

Jung Jin-He (삼성전자(주))
Park Tae-Hyoung (충북대학교 전기전자컴퓨터공학부, 컴퓨터정보통신연구소)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.12, no.3, 2006 , pp. 241-247 More about this Journal
Abstract
We propose a character recognition system to extract the component reference names from printed circuit boards (PCBs) automatically. The names are written in horizontal, vertical, reverse-horizontal and reverse-vertical directions. Also various symbols and figures are included in PCBs. To recognize the character and orientation effectively, we divide the recognizer into two stages: character classification stage and orientation classification stage. The character classification stage consists of two sub-recognizers and a verifier. The rotaion-invarint features of input pattern are then used to identify the character independent of orientation. Each recognizer is implemented as a neural network, and the weight values of verifier are obtained by genetic algorithm. In the orientation classification stage, the input pattern is compared with reference patterns to identify the orientation. Experimental results are presented to verify the usefulness of the proposed system.
Keywords
character recognition; electronic manufacturing system; printed circuit board; neural networks;
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Times Cited By KSCI : 1  (Citation Analysis)
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