DOI QR코드

DOI QR Code

TFT-LCD의 결함 검출을 위한 원근 변환 기반의 패턴 제거 방법

Pattern Elimination Method Based on Perspective Transform for Defect Detection of TFT-LCD

  • 이준재 (계명대학교 게임모바일콘텐츠학과) ;
  • 이광호 (경일대학교 전자공학과) ;
  • 정창도 (타이코에이엠피 연구소) ;
  • 박길흠 (경북대학교 전자전기공학부) ;
  • 박윤범 (서원대학교 수학교육학과) ;
  • 이병국 (동서대학교 컴퓨터정보공학부)
  • 투고 : 2011.12.06
  • 심사 : 2012.04.30
  • 발행 : 2012.06.30

초록

TFT-LCD의 결함은 LCD 패널 자체에 존재하는 패턴으로 인해 원본영상과 입력영상 간의 차영상에 문턱치를 적용하여 검출한다. 그러나 카메라의 특성에 기인한 기하학적인 왜곡에 의해, 패널의 패턴 주기에 해당하는 피치가 영상의 중심에서 멀어질수록 심하게 달라진다. 본 논문에서는 주어진 피치영역의 상하좌우 주변영역과의 비교에 기반한 검출을 제안한다. 이때, 왜곡 보정을 위해 피치계산을 위한 특징점을 추출하고 원근변환을 수행한다. 현장 데이터에 대한 실험을 통해 제안방법의 우수성을 입증한다.

Defects of TFT-LCD is detected by thresholding the difference image between the input image and template one because LCD panel has its inherent patterns. However, the pitch corresponding to pattern period is gradually changed according to the distance from the center of camera due to geometric distortion of camera characteristics. This paper presents a method to detect defects through comparing the pitch area with neighbor pitch areas where the perspective transform is performed with the extracted features to correct the distortion. The experimental results show that the performance of the proposed method is very effective for real data.

키워드

참고문헌

  1. C.J. Lu and D.M. Tsai, "Defect Inspection of Patterned Thin Film Transistor-Liquid Crystal Display Panels Using a Fast-Image- Based Singular Value Decomposition," Int. J . Prod. Res., Vol.42, No.20, pp. 4331-4351, 2004. https://doi.org/10.1080/00207540410001716480
  2. W.K. Pratt, S.S. Sawkar, and Kevin O'Reilly, "Automatic Blemish Detection in Liquid Crystal Flat Panel Displays," SPIE Mach. Vision App. in Industrial Inspection, Vol.3306, pp. 2-13, 1998.
  3. K. Taniguchi and S. Tatsumi, "A Detection Method for Irregular Lightness Variation of Low Contrast," IEEE Systems, Man and Cybernetics, Vol.7, No.3, pp. 6401-6406, 2004
  4. F.H.Y. Chan, F.K. Lam, and H. Zhu, "Adaptive Thresholding by Variational Method," IEEE Transactions on Image Processing, Vol.2, No.3, pp. 168-174, 1998.
  5. J.Y. Lee and S.I. Yoo, "Automatic Detection of Region-Mura Defect in TFT-LCD," IEICE Trans. Inf. & Syst., Vol.87-D, No.10, pp. 2371-2378, 2004.
  6. B.C. Jiang, C.C. Wang, and H.C. Liu, "Liquid Crystal Display Surface Uniformity Defect Inspection using Analysis of Variance and Exponentially Weighted Moving Average Techniques," International Journal of Production Research, Vol.43, No.1, pp. 67-80, 2005. https://doi.org/10.1080/00207540412331285832
  7. K.B. Lee, M.S. Ko, J.J. Lee, T.M. Koo, and K. H.Park, "Defect Detection Method for TFT-LCD Panel Based on Saliency Map Model," IEEE Region 10 Conference, Vol.A, pp. 223-226, 2004.
  8. 김상지, 황용현, 이병국, 이준재, "B-spline 기반의 FPD 패널 결함 검사," 멀티미디어학회논문지, 제10권, 제10호, pp. 1271-1283, 2007.
  9. Z. Yu and Z. Jian, "Fuzzy Recognition of the Defect of TFT-LCD," SPIE Electronic Imaging and Multimedia Technology IV, Vol. 5637, pp. 233-240, 2005.
  10. J.H. Choi, D.M. Kwak, K.B. Lee, and Y.C. Song, "Line Defect Detection in TFT-LCD Using Directional Filter Bank and Adaptive Theresholding," Key Engineering Materials, Vol.270-273, No. 8, pp. 233-238, 2004. https://doi.org/10.4028/www.scientific.net/KEM.270-273.233
  11. H.C. Chen, L.T. Fang, L. Lee, C.H. Wen, S.Y. Cheng, and S.J. Wang, "LOG-Filter-Based Inspection of Cluster Mura and Vertical-Band Mura on Liquid Crystal Displays," SPIE Mach. Vision App. in Industrial Inspection, Vol. 5679, pp. 257-265, 2005.
  12. D.M. Tsai and C.H. Chiang, "Automatic Band Selection for Wavelet Reconstruction in the Application of Defect Detection," Image and Vision Computing, Vol.21, No.5, pp. 413-431, 2003. https://doi.org/10.1016/S0262-8856(03)00003-9

피인용 문헌

  1. Self-Reference PCSR-G Method for Detecting Defect of Flat Panel Display vol.18, pp.3, 2015, https://doi.org/10.9717/kmms.2015.18.3.312
  2. Correction of Perspective Distortion Image Using Depth Information vol.18, pp.2, 2015, https://doi.org/10.9717/kmms.2015.18.2.106
  3. 푸리에 광학의 디스플레이 기판 결함 검출에의 활용 vol.28, pp.1, 2017, https://doi.org/10.3807/kjop.2017.28.1.001
  4. Cutting Blade Measurement of an Ultrasonic Cutting Machine Using Multi-Step Detection vol.9, pp.16, 2012, https://doi.org/10.3390/app9163338