Journal of IKEEE (전기전자학회논문지)

Institute of Korean Electrical and Electronics Engineers (한국전기전자학회)
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FPGA Implementation of Extreme Contour Point Algorithm to detect rotated angle of High Definition Image

고해상 영상의 회전된 각도를 검출하기 위한 Extreme Contour Point 알고리즘의 FPGA 설계

  • Jeong, Min-woo (Dept. of Electronics Engineering, Cheongju University) ;
  • Pack, Chan-su (Dept. of Electronics Engineering, Cheongju University) ;
  • Kim, Hi-Seok (Dept. of Electronics Engineering, Cheongju University)
  • Received : 2016.10.25
  • Accepted : 2016.12.28
  • Published : 2016.12.31
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Abstract

In this Paper, we propose an optimized method of hardware design based on Field Programmable Gate Array (FPGA) to detect rotated angle of high definition image about Extreme Contour Point (ECP) algorithm with moving video image could be not happened to translation motion, but also physical rotation motion. It was evaluated by XC7Z020 xc7z020-3clg400 FPGA board by using xilinx 14.2 tool. The much well-known method, the Coordinate Rotation Digital Integrated Computation (CORDIC) is an algorithm to estimate rotated angle between point and point. Through the result both ECP and CORDIC, our proposed design are confirmed to have similar operating speed of about 4ns with CORDIC. However, it is verified to have high performance result in terms of the hardware cost, is much better than CORDIC with cost reduction of registers and Look Up Tables (LUTs) of 108% and 91%, respectively.

본 논문에서는 움직이는 영상에 대해 물리적인 회전이 발생하였을 때, 빠른 보정을 처리하기 위해 회전된 영상의 회전 각도를 고속으로 처리하기 위한 ECP (Extreme Contour Point) 알고리즘의 FPGA (Field Programmable Gate Array) 하드웨어 설계를 최적화하였고, XC7Z020 xc7z020-3clg400 FPGA 보드와 xilinx 14.2 툴을 사용하여 검증하였다. 잘 알려진 각도 산출 알고리즘인 CORDIC (Coordinate Rotation Digital Integrated Computation)과 비교하여 4ns의 유사한 동작 속도 안에서 CORDIC 대비 Registers는 108%, Look Up Tables (LUTs)는 91% 감소하는 등 하드웨어 비용이 우수함을 확인하였다.

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References

  1. J. McCall and M. Trivedi, "Video-Based Lane Estimation and Tracking for Driver Assistance: Survey, System, and Evaluation," IEEE Trans. Intel. Trans. Syst., vol. 7, no.1, pp. 20-37, 2006. https://doi.org/10.1109/TITS.2006.869595
  2. D. Kim, S. Moon, J. Park, H. Kim and K. Yi, "Design of an Adaptive Cruise Control / Collision Avoidance with Lane Change Support for Vehicle Autonomous Driving," Proceedings of ICRO-SCIE International Joint Conference, pp. 2938-2943, 2009
  3. K. Shimura, K. ohtsuka, G. Vizzari, K. Nishinari and S. Bandini, "Mobility analysis of the aged pedestrians by experiment and simulation," Patt. Recognit. Lett. vol. 44, pp. 58-63, 2014. https://doi.org/10.1016/j.patrec.2013.10.027
  4. L. Oliveriara and U. Nunes, "Context-aware Pedestrian Detection Using LIDAR," Proceedings of IEEE Intelligent Vehicles Symposium, pp. 773-778, 2010.
  5. D. Han, M. Jeong, and H. Kim, "A Novel Implementation of Rotation Detection Algorithm using a polar Representation of Extreme Contour Point based on Sobel Edge," Journal of Semiconductor Technology and Science, In press, 2016.
  6. C. Park and H. Kim, "FPGA Implementation for Real Tiome Sobel Edge Detector Block Using 3-Line Buffers," j.inst.Korean.electr. electron.eng, vol.19, no. 1, pp. 10-17, 2015.
  7. J. Volder, "The CORDIC Computing Technique," IRE Trans. Electron. Comput, vol. 8, no. 3, pp. 330-334, 1959.