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Resolution improvement of a CMOS vision chip for edge detection by separating photo-sensing and edge detection circuits

수광 회로와 윤곽 검출 회로의 분리를 통한 윤곽 검출용 시각칩의 해상도 향상

  • Kong, Jae-Sung (Department of Electronics, Kyungpook National University) ;
  • Suh, Sung-Ho (System LSI Division, Samsung Electronics Co., Ltd.) ;
  • Kim, Sang-Heon (Department of Electronics, Kyungpook National University) ;
  • Shin, Jang-Kyoo (Department of Electronics, Kyungpook National University) ;
  • Lee, Min-Ho (Department of Electronics, Kyungpook National University)
  • Published : 2006.03.31

Abstract

Resolution of an image sensor is very significant parameter to improve. It is hard to improve the resolution of the CMOS vision chip for edge detection based on a biological retina using a resistive network because the vision chip contains additional circuits such as a resistive network and some processing circuits comparing with general image sensors such as CMOS image sensor (CIS). In this paper, we proved the problem of low resolution by separating photo-sensing and signal processing circuits. This type of vision chips occurs a problem of low operation speed because the signal processing circuits should be commonly used in a row of the photo-sensors. The low speed problem of operation was proved by using a reset decoder. A vision chip for edge detection with $128{\times}128$ pixel array has been designed and fabricated by using $0.35{\mu}m$ 2-poly 4-metal CMOS technology. The fabricated chip was integrated with optical lens as a camera system and investigated with real image. By using this chip, we could achieved sufficient edge images for real application.

Keywords

References

  1. Alireza Moini, Vision Chips or Seeing Silicon, CHiPTec, 1997
  2. C. A. Mead, Analog VISI and Neural Systems, Addison-Wesley, 1989
  3. Lotufo, R.A., Morgan, A.D., and Johnson, A.S. 'Automatic number-plate recognition', IEEE Colloquium on Image Analysis for Transport Applications, pp. 6/1-6/6, 1990
  4. Monica A. Trifas and John M. Tyler, 'Medical image enhancement', Conf. on Computer Vision, pp. 212-218, 2005
  5. J. Alves, J. Herman, and N.C. Rowe, 'Robust recognition of ship types from an infrared silhouette', Command and Control Research and Technology Symposium, San Diego, Jun. 2004
  6. S. K. Mendis, S. E. Kemeny, R. C. Gee, B. Pain, C. O. Staller, Q. Kim, and E. R. Fossum, 'CMOS active pixel image sensors for highly integrated imaging systems', IEEE Journal of Solid-State Circuits, vol. 32, pp. 187-197, Feb. 1997 https://doi.org/10.1109/4.551910
  7. C. Y. Wu and C. F. Chiu, 'A new structure of the 2-D silicon retina', IEEE J. Solid-State Circuits, vol. 30, pp. 890-897, 1995 https://doi.org/10.1109/4.400431
  8. H. S. Kim, D. S. Park, B. W. Ryu, S. K. Lee, M. H. Lee, and J. K. Shin, 'Design and fabrication of 8xg foveated CMOS retina chip for edge detection', J. of the Korean Sensors Society, vol. 10, pp. 91-100, 2001
  9. D. S. Park, K. M. Kim, S. K. Lee, H. S. Kim, J. H. Kim, M. H. Lee, and J. K. shin, 'Design and fabrication of 32 x 32 foveated CMOS retina chip for edge detection with local-light adaptation', J. of the Korean Sensors Society, vol. 11, pp. 84-92, 2002 https://doi.org/10.5369/JSST.2002.11.2.084
  10. S.-H. Suh, J.-H. Kim, J.-S. Kong, and J.-K. Shin, 'Vision chip for edge detection with a function of pixel FPN reduction', J. of the Korean Sensors Society, vol. 14, no. 3, pp. 191-197, 2005 https://doi.org/10.5369/JSST.2005.14.3.191
  11. S. Kameda, A. Honda, and T. Yagi, 'Real time image processing with an analog vision chip system', International Journal of Neural Systems, vol. 9, no. 5, pp. 423-428. 1999 https://doi.org/10.1142/S0129065799000423
  12. Marcel J. M. Pelgrom, Aad C. J. Duinmaijer, and Anton P. G. Welbers, 'Matching properties of MOS transistors', IEEE J. Solid-State Circuits, vol. 24, no. 5, pp. 1433-1440, 1989 https://doi.org/10.1109/JSSC.1989.572629
  13. S. Kavadias, 'Offset-free column readout circuit for CMOS image sensors', Electronics Letters, vol. 35, no. 24, pp. 2112-2113, 1999 https://doi.org/10.1049/el:19991453

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