Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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Improved Statistical Grey-Level Models for PCB Inspection

PCB 검사를 위한 개선된 통계적 그레이레벨 모델

  • Bok, Jin Seop (Korea University of Technology and Education, School of Computer Engineering) ;
  • Cho, Tai-Hoon (Korea University of Technology and Education, School of Computer Engineering)
  • 복진섭 (한국기술교육대 컴퓨터공학부) ;
  • 조태훈 (한국기술교육대 컴퓨터공학부)
  • Received : 2013.01.03
  • Accepted : 2013.02.28
  • Published : 2013.03.31
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Abstract

Grey-level statistical models have been widely used in many applications for object location and identification. However, conventional models yield some problems in model refinement when training images are not properly aligned, and have difficulties for real-time recognition of arbitrarily rotated models. This paper presents improved grey-level statistical models that align training images using image or feature matching to overcome problems in model refinement of conventional models, and that enable real-time recognition of arbitrarily rotated objects using efficient hierarchical search methods. Edges or features extracted from a mean training image are used for accurate alignment of models in the search image. On the aligned position and orientation, fitness measure based on grey-level statistical models is computed for object recognition. It is demonstrated in various experiments in PCB inspection that proposed methods are superior to conventional methods in recognition accuracy and speed.

Keywords

References

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