Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Defect Detection Method using Human Visual System and MMTF

MMTF와 인간지각 특성을 이용한 결함성분 추출기법

  • Huh, Kyung-Moo (Department of Electronic Engineering, Dankook University) ;
  • Joo, Young-Bok (Department of Computer Science & Engineering, Korea University of Technology & Education)
  • 허경무 (단국대학교 전자공학과) ;
  • 주영복 (한국기술교육대학교 컴퓨터공학부)
  • Received : 2013.08.20
  • Accepted : 2013.10.04
  • Published : 2013.12.01
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Abstract

AVI (Automatic Vision Inspection) systems automatically detect defect features and measure their sizes via camera vision. Defect detection is not an easy process because of noises from various sources and optical distortion. In this paper the acquired images from a TFT panel are enhanced with the adoption of an HVS (Human Visual System). A human visual system is more sensitive on the defect area than the illumination components because it has greater sensitivity to variations of intensity. In this paper we modified an MTF (Modulation Transfer Function) in the Wavelet domain and utilized the characteristics of an HVS. The proposed algorithm flattens the inner illumination components while preserving the defect information intact.

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References

  1. E. N. Malamas, E. G. M. Patrakis, M. Zervakis, L. Petit, and J. D. Legat, "A survey on industrial vision systems, applications and tools," Image and Vision Computing, vol. 21, no. 2, pp. 171-188, Feb. 2003. https://doi.org/10.1016/S0262-8856(02)00152-X
  2. R. Sablatnig, "A flexible concept for automatic visual inspection," Czech Pattern Recognition Workshop'97, Proc. of (CPRW'97), 1997.
  3. J. H. N. Mattick, R. W. Kelsall, and R. E. Miles, "Improved critical area prediction by application of pattern recognition techniques," Microelectronics Robustness, vol. 36, no. 11-12, pp. 1815-1818, Dec. 1996.
  4. H. F. Ng, "Automatic thresholding for defect detection," Pattern Recognition Letters, vol. 27, no. 14, pp. 1644-1649, Oct. 2006. https://doi.org/10.1016/j.patrec.2006.03.009
  5. G. A. Allan and A. J. Walton, "Efficient critical area estimation for arbitrary defect shapes," Workshop on Defect and Fault- Tolerance in VLSI Systems (DFT '97). vol. 7, no. 3, pp. 284-292, Aug. 1994.
  6. W. Zhu, Q. L. Cao, J. Rhodes, and Z. M. Hijazi, "Measurement atrial septal defect size: a comparative study between threedimensional tranesophageal echocardiography and the standard balloonsizing methods," Pediatric Cardiology, vol. 21, no. 5, pp. 465-469, Sep. 2000. https://doi.org/10.1007/s002460010111
  7. S.-H. Kim, I.-K. Jung, C.W. Park, and J.-H. Hwang, "Efficient object tracking system using the fusion of a CCD camera and an infrared camera," Journals of Institute of Control, Robotics and Systems (in Korean), vol. 17, no. 3, pp. 229-235, Mar. 2011. https://doi.org/10.5302/J.ICROS.2011.17.3.229
  8. D. W. Lee, J. H. Kim, and H. J. Kim, "Depth estimation for image-based visual servoing of an under-actuated system," Journals of Institute of Control, Robotics and Systems (in Korean), vol. 18, no. 1, pp. 42-46, Jan. 2012. https://doi.org/10.5302/J.ICROS.2012.18.1.042
  9. G. S. Kim, S. Lee, J.-S. Park, and J.-S. Cho, "Study on effective visual surveillance system using dual-mode (Fixed+Pan/ Tilt/Zoom) camera," Journals of Institute of Control, Robotics and Systems (in Korean), vol. 18, no. 7, pp. 650-657, Jul. 2012. https://doi.org/10.5302/J.ICROS.2012.18.7.650