Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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A Hardware Design for Realtime Correction of a Barrel Distortion Using the Nearest Pixels on a Corrected Image

보정 이미지의 최 근접 좌표를 이용한 실시간 방사 왜곡 보정 하드웨어 설계

  • Song, Namhun (Dept. of Computer Engineering, Kwangwoon University) ;
  • Yi, Joonhwan (Dept. of Computer Engineering, Kwangwoon University)
  • 송남훈 (광운대학교 컴퓨터공학과) ;
  • 이준환 (광운대학교 컴퓨터공학과)
  • Received : 2012.11.29
  • Accepted : 2012.12.16
  • Published : 2012.12.31
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Abstract

In this paper, we propose a hardware design for correction of barrel distortion using the nearest coordinates in the corrected image. Because it applies the nearest distance on corrected image rather than adjacent distance on distorted image, the picture quality is improved by the image whole area, solve the staircase phenomenon in the exterior area. But, because of additional arithmetic operation using design of bilinear interpolation, required arithmetic operation is increased. Look up table(LUT) structure is proposed in order to solve this, coordinate rotation digital computer(CORDIC) algorithm is applied. The results of the synthesis using Design compiler, the design of implementing all processes of the interpolation method with the hardware is higher than the previous design about the throughput, In case of the rear camera, the design of using LUT and hardware together can reduce the size than the design of implementing all processes with the hardware.

본 논문은 보정 이미지에서 최 근접 좌표를 이용한 방사 왜곡 보정 하드웨어 구조를 제안한다. 기존 보간법과는 달리 보정 이미지에서 최근접한 좌표의 거리를 이용하기 때문에 이미지 전체 영역의 화질 향상과 함께 외각영역에서 발생하는 계단 현상을 해결할 수 있다. 그러나 양 선형 보간법을 적용한 기존 구조에서 추가되는 연산으로 인해 하드웨어 크기가 증가한다. 이를 해결하기 위해 룩 업 테이블 구조를 제안하고, 코르딕 알고리즘을 적용한다. Design compiler를 이용하여 합성한 결과 보간법의 모든 과정을 하드웨어로 구현한 구조는 기존 구조에 비해 처리량이 높고, 차량용 후방 카메라의 경우 룩 업 테이블과 하드웨어를 함께 사용한 구조는 모든 과정을 하드웨어로 구현한 구조보다 하드웨어 크기를 10% 줄일 수 있다.

Keywords

References

  1. S. Chen, H. Huang, and C. Luo, "Time multiplexed VLSI architecture for realtime barrel distortion correction in video endoscopic images," Circuits and Systems for Video Technology, IEEE Trans. on, Vol 21, No 11, pp. 1612-1621, November 2011. https://doi.org/10.1109/TCSVT.2011.2129850
  2. W. Feng, Y. Liu, "Omnidirectional vision tracking and positioning for vehicles," Natural Computation, 2008. ICNC '08. Fourth International Vol 6, pp. 183 -187, October 2008.
  3. X. ming Dong, "Landmark design and realtime recognition based on fisheye image for robot navigation," Computer Engineering and Technology (ICCET), 2010 2nd International Conference on, Vol 1, pp. 437-440, April 2010.
  4. J. Brauers, "Geometric calibration of lens and filter distortions for multispectral filter wheel cameras," IEEE Trans on Image Processing, Vol 20, No 2, pp. 496-505, February 2011. https://doi.org/10.1109/TIP.2010.2062193
  5. T. Rahman, "An efficient camera calibration technique offering robustness and accuracy over a wide range of lens distortion," IEEE Trans on Image Processing, Vol 21, No 2, pp. 626-637, February 2012. https://doi.org/10.1109/TIP.2011.2164421
  6. Zijian Zhao, "Camera calibration with three noncollinear points under special motions," IEEE Transactions on Image Processing, Vol 17, No 12, pp. 2393-2402, December 2008. https://doi.org/10.1109/TIP.2008.2005562
  7. K. Y. Shin, "Multi camera calibration method for optical motion capture system," Journal of the Korea society of computer and information, Vol 14, No 6, pp. 41-49, June 2009.
  8. M. Ahmed, "Nonmetric calibration of camera lens distortion: differential methods and robust estimation," IEEE Transactions on Image Processing, Vol 14, No 8, pp. 1215-1230, August 2005. https://doi.org/10.1109/TIP.2005.846025
  9. K. Johnson, P. W. Smith, and M. A. Abidi, "A quadric surface projection model for wide angle lenses," Proc. of SPIE Conf. on Intelligent Robots, and Computer Vision XVII: Algorithms, Techniques, and Active Vision, Vol. 3522, Boston, MA, November. 1999, pp. 424-434.
  10. M. Sone, N. Sudo, H. Yokotsuka, "Comparison of image interpolation methods applied to least squares matching," Computational Intelligence for Modelling Control & Automation, 2008 Internation al Conference on, pp. 1017-1022, December 2008.
  11. S. M. Jung, "Quality improvement scheme of interpolated image using the characteristics of the adjacent pixels," Journal of the Korea society of computer and information, Vol 16, No 11, pp. 95-102, October 2011. https://doi.org/10.9708/jksci.2011.16.11.095
  12. J. Y. Han, "Fisheye image correction and low power scaler design," master's thesis, Kwangwoon University, 2010.
  13. Y. J. Lee, "Near pixels fisheye lens image correction based on near pixels of a corrected image,"master's thesis, Kwangwoon University, 2011.
  14. K. Vijayan Asari, "Design of an efficient VLSI architecture for non linear spatial warping of wide angle camera images," Journal of Systems Architecture, Vol. 50, No 12, pp. 743-755, August 2004. https://doi.org/10.1016/j.sysarc.2004.05.001
  15. H. T. Ngo and V. K. Asari, "A pipelined archi tecture for realtime correction of barrel distortion in wide angle camera images," IEEE Trans. Circuits Syst. Video Techno., Vol. 15, No. 3, pp. 436-444, March 2005. https://doi.org/10.1109/TCSVT.2004.842609
  16. P. Y. Chen, C. C. Huang, Y. H. Shiau, and Y.T. Chen,"A VLSI implementation of barrel distortion correction for wide angle camera images," IEEE Trans. Circuits Syst. 2 Express Briefs, Vol. 56, No. 1, pp. 51-55, January 2009. https://doi.org/10.1109/TCSII.2008.2010165
  17. Synopsys Inc, "DesignWare building block IP." [Online]. Available: http://www.synopsys.com
  18. J. Volder, "The CORDIC trigonometric computing technique," Electronic Computers, IRE Transactions on, Vol EC-8, No 3, pp. 330-334, September 1959. https://doi.org/10.1109/TEC.1959.5222693
  19. Kodak lossless true color image, http://r0k.us/graphics/kodak