대한임베디드공학회논문지 (IEMEK Journal of Embedded Systems and Applications)

대한임베디드공학회 (Institute of Embedded Engineering of Korea)
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Automatic Display Defect Detection System Using Image Processing

  • 권동욱 ;
  • 손혜원 ;
  • 전소연 ;
  • 이원일
  • Dong-Uk Kwon (Kumoh National Institute of Technology) ;
  • Hye-Won Son (Kumoh National Institute of Technology) ;
  • So-Yeon Jeon (Kumoh National Institute of Technology) ;
  • Won Il Lee (Kumoh National Institute of Technology)
  • 투고 : 2024.06.30
  • 심사 : 2024.09.11
  • 발행 : 2024.10.31
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초록

In this paper, we propose an automatic display defect detection system using image processing. The existing inspection by operators has the disadvantage that human errors may occur due to the operator's skill level, fatigue, etc., and that standardization and quantification are difficult. It also has disadvantages such as the limited inspection speed and the cost of the operator's education. The proposed system automatically detects various display defects through image processing algorithms. It was developed based on the Jetson Nano, one of the most popular SBCs (Single Board Computers), and it has a conveyor belt to automatically moves the display to the inspection position. By providing a human machine interface (HMI), the operator can check the inspection information in real time, and control the inspection flow. By storing the inspection results as a log file, the operator can check the inspection results at any time, such as the time taken to perform each algorithm and the location of the detected defects. In addition, a multi-threaded structure was adopted. The camera's operations and inspection algorithms are executed in parallel in different threads, which can shorten the inspection time compared to the system based on a single-threaded structure. The experimental results prove the defect detection capability of the system and the efficiency of the inspection time.

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과제정보

이 연구는 국립금오공과대학교 대학 연구과제비로 지원되었음 (2021).

참고문헌

  1. G. H. Jo, Y. W. Heo, Y. J. Song, "Image Extraction Method for Defect Detection of Display Panel," The Proceedings of the 2021 KIIT Autumn Conference, pp. 246-248, 2021 (in Korean).
  2. G. H. Jo, Y. W. Heo, H. W. Cho, Y. J. Song, "Implementation of OLED Display Defect Detection System using CNN," Journal of KIIT., Vol. 20, No. 6, pp. 1-8, 2022 (in Korean).
  3. E. Y. Lee, K. H. Park, "Mura Defect Enhancement based on Saliency Map in TFT-LCD Image," Journal of Korea Multimedia Society, Vol. 19, No. 3, pp. 626-632, 2016 (in Korean).
  4. C. S. Hwang, "Technology Trends in Spatial Display," Journal of Broadcast and Media Magazine, Vol. 27, No. 4, pp. 66-78, 2022 (in Korean).
  5. H. J. Lee, T. H. Park, "Mura Defect Detection of Display Panel Using Gabor Wavelet Transformation and Image Post-Processing," Journal of Institute of Control, Robotics and Systems, Vol. 23, No. 4, pp. 287-293, 2017 (in Korean).
  6. C. Oh, Y. K. Ryu, S. J. Shin, H. J. Yoo, B. U. Jun, "An Algorithm Development for Detecting Blister Defects of Display Glasses," Journal of the Korean Society for Precision Engineering, Vol. 24, No. 4, pp. 15-20, 2007 (in Korean).
  7. H. Gu, J. W. Yun, J. W. Bae, T. H. Kim, S. J. Ko, "A New Feature Extraction Method for Mura Defect Classification," Autumn Annual Conference of IEIE, pp. 445-447, 2013 (in Korean).
  8. S. Bae, J. S. Seok, M. S. Lee, J. S. Kim, "PCB Visual Inspection Using OpenVX-based Vision Processing and Machine Learning," The Proceedings of the 2021 KICS Summer Conference, pp. 918-919, 2021 (in Korean).
  9. S. M. Lee, T. H. Kim, K. H. Park, "Sequential Defect Detection According to Defect Possibility in TFT-LCD Panel Image," Journal of The Institute of Electronics and Information Engineers, Vol. 51, No. 4, pp. 799-806, 2014 (in Korean).
  10. J. H. Kim, T. Y. Lee, Y. H. Ko, "Self-Reference PCSR-G Method for Detecting Defect of Flat Panel Display," Journal of Korea Multimedia Society, Vol. 18, No. 3, pp. 312-322, 2015 (in Korean).
  11. S. H. Cho, H. B. Kang, "Automatic TFT-LCD Mura Defect Detection Using Gabor Wavelet Transform and DCT," JBE Vol. 18, No. 4, pp. 525-534, 2013 (in Korean).
  12. Y. J. Jung, K. Lee, "Application of Fourier Optics to Defect Inspection of Display Substrates," Korean Journal of Optics and Photonics, Vol. 28, No. 1, pp. 1-8, 2017 (in Korean).
  13. A. Gaybulayev, N. H. Lee, K. H. Lee, T. H. Kim, "Development of a Steel Plate Surface Defect Detection System Based on Small Data Deep Learning," IEMEK J. Embed. Sys. Appl., Vol. 17, No. 3, pp. 129-138, 2022 (in Korean).