• DocumentCode
    1776196
  • Title

    Real-time traffic sign recognition based on Zynq FPGA and ARM SoCs

  • Author

    Yan Han ; Oruklu, Erdal

  • Author_Institution
    Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA
  • fYear
    2014
  • fDate
    5-7 June 2014
  • Firstpage
    373
  • Lastpage
    376
  • Abstract
    In this paper, an FPGA-based traffic sign recognition system is introduced for driver assistance applications. The system incorporates two major operations, traffic sign detection and recognition. The algorithms presented include hue detection for potential sign detection, morphological filters for noise reduction, labeling and Hausdorff distance calculation for template recognition. A new hardware platform is presented that combines a Zynq-7000 FPGA processing system and custom IP peripherals together. A frame-work for embedded system development on ARM CPU cores and FPGA fabric is introduced. The proposed hardware platform achieves up to 8 times speed-up compared to the existing FPGA based solutions.
  • Keywords
    field programmable gate arrays; image colour analysis; object detection; object recognition; system-on-chip; traffic engineering computing; ARM CPU cores; ARM SoC; FPGA fabric; FPGA-based traffic sign recognition system; Hausdorff distance calculation; Zynq-7000 FPGA processing system; custom IP peripherals; driver assistance applications; embedded system development; hardware platform; hue detection; labeling; morphological filters; noise reduction; real-time traffic sign recognition; template recognition; traffic sign detection; Field programmable gate arrays; Hardware; IP networks; Image color analysis; Real-time systems; Registers; Software; FPGA implementation; image processing; traffic sign recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electro/Information Technology (EIT), 2014 IEEE International Conference on
  • Conference_Location
    Milwaukee, WI
  • Type

    conf

  • DOI
    10.1109/EIT.2014.6871793
  • Filename
    6871793