• 제목/요약/키워드: PCSR-G

검색결과 2건 처리시간 0.02초

평판 디스플레이 결함 검출을 위한 자기 참조 PCSR-G 기법 (Self-Reference PCSR-G Method for Detecting Defect of Flat Panel Display)

  • 김진형;이태영;고윤호
    • 한국멀티미디어학회논문지
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    • 제18권3호
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    • pp.312-322
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    • 2015
  • In this paper a new defect detection method for flat panel display that does not require any separately prepared reference images and shows robustness against problems with regard to pixel tolerance and nonuniform illumination condition is proposed. In order to perform defect detection under any magnification value of camera, the proposed method automatically obtains the value of pattern interval through an image analysis. Using the information for pattern interval, an advanced PCSR-G method presented in this paper utilizes neighboring patterns as its reference images instead of utilizing any separately prepared reference images. Also this paper proposes a scheme to improve the performance of the conventional PCSR-G method by extracting and applying additional information for pixel tolerance and intensity distribution considering the value of pattern interval. Simulation results show that the performance of the proposed method utilizing pixel tolerance and intensity distribution is superior to that of the conventional method. Also, it is proved that the proposed method that is implemented using parallel technique based on GPGPU can be applied to real system.

패턴 비교를 통한 TFT-LCD 패널의 결함 검출 방법 (A New Defect Inspection Method for TFT-LCD Panel using Pattern Comparison)

  • 이경민;장문수;박부견
    • 전기학회논문지
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    • 제57권2호
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    • pp.307-313
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    • 2008
  • In this paper, we propose a novel defects inspection algorithm for TFT-LCD panels. We first compensate the distorted image caused by the camera distortion and the uneven illumination environment using the least squares method and the bezier surface. We find a starting point of each pattern for restricting each pattern. A clean image is compared to each pattern to find defects using modified PCSR-G algorithm. The simulation example shows that our algorithm not only inspects the defects well, but also is robust to the 1-pixel error.