Journal of Advanced Marine Engineering and Technology

The Korean Society of Marine Engineering (한국마린엔지니어링학회)
권호 표지
DOI QR코드

DOI QR Code

Defect detection based on periodic cell pattern elimination in TFT-LCD cell images

TFT-LCD 셀 영상에서 주기적인 셀 패턴 제거 기반 결함검출

  • Jung, Yeong-Tak (Defense Agency for Technology and Quality) ;
  • Lee, Seung-Min (School of Electronics Engineering, Kyungpook National University) ;
  • Park, Kil-Houm (School of Electronics Engineering, Kyungpook National University)
  • Received : 2017.02.21
  • Accepted : 2017.03.16
  • Published : 2017.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, an algorithm for detecting defects in thin-film-transistor liquid-crystal display (TFT-LCD) cell images is presented. TFT-LCD cell images typically contain periodic cell patterns that make it difficult to detect defects. We propose an efficient and powerful algorithm for eliminating the cell patterns using magnitude spectrum analysis. The first step was to obtain a spectrum for a cell image using the Fourier transform while eliminating larger coefficients using an adaptive filter. Next, an image without the cell pattern was obtained by using the inverse Fourier transform. Finally, the defect pixels were detected using the STD algorithm. The validity of the proposed method was investigated using real TFT-LCD cell images. The experimental results indicate that the proposed technique is extremely effective for detecting defects in TFT-LCD cell images.

본 논문에서는 TFT-LCD 셀 영상에서 퓨리에 변환을 이용한 주기적인 셀 패턴 제거에 기반한 결함검출 방법을 제안한다. 셀 영상은 결함검출을 어렵게 하는 주기적인 셀 패턴을 포함하므로 패턴 제거가 중요하다. 먼저 셀 영상에 대해 퓨리에 변환을 이용하여 스펙트럼을 구하고, 스펙트럼에서 큰 값의 계수는 셀 패턴에 관련된 계수이므로 적응적 필터를 이용하여 큰 값의 계수를 제거한다. 그리고 필터링된 스펙트럼을 역 퓨리에 변환을 이용하여 셀 패턴이 제거된 영상을 얻는다. 다음으로 셀 패턴이 제거된 영상에서 STD 방법으로 결함을 검출한다. TFT-LCD 셀 영상에 대해 제안 방법의 타당성을 검증한 결과, 제안 방법이 우수한 결함검출 성능을 가짐을 확인하였다.

Keywords

References

  1. J. Jang, S. K. Lim, and M. H. Oh, "Technology development and production of flat panel displays in Korea," Proceedings of the IEEE. vol. 90, no. 4, pp. 501-513, 2002. https://doi.org/10.1109/JPROC.2002.1002522
  2. C. B. Moon, Y. H. Ahn, H. Y. Lee, B. M. Kim, and D. W. Oh, "Implementation of automatic detection system for CCFL's defects based on combined lighting," Journal of the Korea Industrial Systems Research, vol. 15, no. 2, pp. 69-80, 2010 (in Korean).
  3. 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," Proceedings of IEEE Region 10 Conference, pp. 223-226, 2004.
  4. Y. H. Liu, S. H. Lin, Y. L. Hsueh, and M. J. Lee, "Automatic target defect identification for TFT-LCD array process inspection using kernel FCM-based fuzzy SVDD ensemble," Expert Systems with Applications, vol. 36, no. 2, pp. 1978-1998, 2009. https://doi.org/10.1016/j.eswa.2007.12.015
  5. S. L. Chen and S. T. Chou, "TFT-LCD mura defect detection using wavelet and cosine transforms," Journal of Advanced Mechanical Design, Systems, and Manufacturing, vol. 2, no. 3, pp. 441-453, 2008. https://doi.org/10.1299/jamdsm.2.441
  6. W. S. Kim, D. M. Kwak, Y. C. Song, D. H. Choi, and K. H. Park, "Detection of spot-type defects on liquid crystal display modules," Key Engineering Materials, vol. 270, pp. 808-813, 2004.
  7. S. Uchikoga and N. Ibaraki, "Low temperature poly-Si TFT-LCD by excimer laser anneal," Thin Solid Films, vol. 383, no. 1, pp. 19-24, 2001. https://doi.org/10.1016/S0040-6090(00)01644-8
  8. E. M. Stein and G. Weiss, "Introduction to fourier analysis on euclidean spaces," Princeton University Press, vol. 32, 2016.