FPGA Implementation of a Vision-Based Blind Spot Warning System
Vision-based intelligent vehicle applications often require large amounts of memory to handle video streaming and image processing, which in turn increases complexity of hardware and software. This paper presents an FPGA implement of a vision-based blind spot warning system. Using video frames, the information of the blind spot area turns into one-dimensional information. Analysis of the estimated entropy of image allows the detection of an object in time. This idea has been implemented in the XtremeDSP video starter kit. The blind spot warning system uses only 13% of its logic resources and 95k bits block memory, and its frame rate is over 30 frames per sec (fps).
[1] Uvais Qidwai, "Fuzzy Blind-Spot Scanner for Automobiles" in IEEE
Symposium on Industrial Electronics and Applications, October 4-6,
2009, pp. 758-763.
[2] Y. K. Wang and S. H. Chen, "A Robust Vehicle Detection Approach," in
Proc. Int. IEEE Conf. Advanced Video and Signal-based Surveillance,
Sep. 15-16, 2005, pp. 117-122.
[3] Y. Zhu, D. Comaniciu, M. Pellkofer and T. Koehler, "Reliable Detection
of Overtaking Vehicles Using Robust Information Fusion", IEEE Trans.
Intelligent Transportation Systems, vol. 7, no. 4, pp. 401-414, 2007.
[4] A.Techmer, "Real-time Motion Analysis for Monitoring the Rear and
Lateral Road", in Proc. IEEE Intelligent Vehicles Symposium, Jun.
14-17, 2004, pp. 704 - 709.
[5] L. W. Tsai, J. W. Hsieh and K. C. Fan, "Vehicle detection using
normalized color and edge map," in Proc. Int. IEEE Conf. Image
Processing, Sep. 11-14, 2005, vol.2, pp.588-601.
[6] K. She, G. Bebis, H. Gu and R. Miller, "Vehicle Tracking Using On-Line
Fusion of Color and Shape Features," in Proc. 7th Int. IEEE Conf. on
Intelligent Transportation Systems, Oct. 3-6, 2004, pp. 731-736.
[7] P. H. Batavia, D. E. Pomerleau and C. E. Thorpe, "Overtaking Vehicle
Detection Using Implicit Optical Flow," in Proc. IEEE Conf. on
Intelligent Transportation Systems, Nov. 9-12, 1997, pp. 729-734.
[8] M. Krips et al, "AdTM tracking for blind spot collision avoidance", in
Proc. IEEE Intelligent Vehicles Symposium., Jun. 14-17, 2004, pp. 544 -
548.
[9] C.T. Chen and Y.S. Chen, "Real-time approaching vehicle detection in
blind-spot area", in Proc. 12th Int. IEEE Conf. on Intelligent
Transportation Systems, Oct. 4-7, 2009, pp. 1-6.
[10] Sudhir Sharma, Wang Chen, "Using Model-Based Design to Accelerate
FPGA Development for Automotive Applications", in 2009 SAE World
Congress, January 1-15,2009.
[1] Uvais Qidwai, "Fuzzy Blind-Spot Scanner for Automobiles" in IEEE
Symposium on Industrial Electronics and Applications, October 4-6,
2009, pp. 758-763.
[2] Y. K. Wang and S. H. Chen, "A Robust Vehicle Detection Approach," in
Proc. Int. IEEE Conf. Advanced Video and Signal-based Surveillance,
Sep. 15-16, 2005, pp. 117-122.
[3] Y. Zhu, D. Comaniciu, M. Pellkofer and T. Koehler, "Reliable Detection
of Overtaking Vehicles Using Robust Information Fusion", IEEE Trans.
Intelligent Transportation Systems, vol. 7, no. 4, pp. 401-414, 2007.
[4] A.Techmer, "Real-time Motion Analysis for Monitoring the Rear and
Lateral Road", in Proc. IEEE Intelligent Vehicles Symposium, Jun.
14-17, 2004, pp. 704 - 709.
[5] L. W. Tsai, J. W. Hsieh and K. C. Fan, "Vehicle detection using
normalized color and edge map," in Proc. Int. IEEE Conf. Image
Processing, Sep. 11-14, 2005, vol.2, pp.588-601.
[6] K. She, G. Bebis, H. Gu and R. Miller, "Vehicle Tracking Using On-Line
Fusion of Color and Shape Features," in Proc. 7th Int. IEEE Conf. on
Intelligent Transportation Systems, Oct. 3-6, 2004, pp. 731-736.
[7] P. H. Batavia, D. E. Pomerleau and C. E. Thorpe, "Overtaking Vehicle
Detection Using Implicit Optical Flow," in Proc. IEEE Conf. on
Intelligent Transportation Systems, Nov. 9-12, 1997, pp. 729-734.
[8] M. Krips et al, "AdTM tracking for blind spot collision avoidance", in
Proc. IEEE Intelligent Vehicles Symposium., Jun. 14-17, 2004, pp. 544 -
548.
[9] C.T. Chen and Y.S. Chen, "Real-time approaching vehicle detection in
blind-spot area", in Proc. 12th Int. IEEE Conf. on Intelligent
Transportation Systems, Oct. 4-7, 2009, pp. 1-6.
[10] Sudhir Sharma, Wang Chen, "Using Model-Based Design to Accelerate
FPGA Development for Automotive Applications", in 2009 SAE World
Congress, January 1-15,2009.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:50030", author = "Yu Ren Lin and Yu Hong Li", title = "FPGA Implementation of a Vision-Based Blind Spot Warning System", abstract = "Vision-based intelligent vehicle applications often require large amounts of memory to handle video streaming and image processing, which in turn increases complexity of hardware and software. This paper presents an FPGA implement of a vision-based blind spot warning system. Using video frames, the information of the blind spot area turns into one-dimensional information. Analysis of the estimated entropy of image allows the detection of an object in time. This idea has been implemented in the XtremeDSP video starter kit. The blind spot warning system uses only 13% of its logic resources and 95k bits block memory, and its frame rate is over 30 frames per sec (fps).
", keywords = "blind-spot area, image, FPGA", volume = "4", number = "12", pages = "1331-5", }
