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H. Bay, A. Ess, T. Tuytelaars and L. Van Gool, “SpeededUp Robust Features (SURF),”
Computer Vision and Image Understanding, Vol. 110, No. 3, 2008, pp. 346-359.
doi:10.1016/j.cviu.2007.09.014

has been cited by the following article:

• TITLE: FPGA-Based Traffic Sign Recognition for Advanced Driver Assistance Systems

  AUTHORS: Sheldon Waite, Erdal Oruklu

  KEYWORDS: Traffic Sign Recognition; Advanced Driver Assistance Systems; Field Programmable Gate Array (FPGA)

  JOURNAL NAME: Journal of Transportation Technologies, Vol.3 No.1, January 23, 2013

  ABSTRACT: This paper presents the implementation of an embedded automotive system that detects and recognizes traffic signs within a video stream. In addition, it discusses the recent advances in driver assistance technologies and highlights the safety motivations for smart in-car embedded systems. An algorithm is presented that processes RGB image data, extracts relevant pixels, filters the image, labels prospective traffic signs and evaluates them against template traffic sign images. A reconfigurable hardware system is described which uses the Virtex-5 Xilinx FPGA and hardware/software co-design tools in order to create an embedded processor and the necessary hardware IP peripherals. The implementation is shown to have robust performance results, both in terms of timing and accuracy.