Energy-Efficient Hardware Implementation of Road-Lane Detection Based on Hough Transform with Parallelized Voting Procedure and Local Maximum Algorithm

Jungang GUAN  Fengwei AN  Xiangyu ZHANG  Lei CHEN  Hans Jürgen MATTAUSCH  

IEICE TRANSACTIONS on Information and Systems   Vol.E102-D   No.6   pp.1171-1182
Publication Date: 2019/06/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDP7279
Type of Manuscript: PAPER
Category: Image Processing and Video Processing
Hough transform,  paralleled voting-procedure,  local maximum,  video-based road-lane detection,  energy efficient,  

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Efficient road-lane detection is expected to be achievable by application of the Hough transform (HT) which realizes high-accuracy straight-line extraction from images. The main challenge for HT-hardware implementation in actual applications is the trade-off optimization between accuracy maximization, power-dissipation reduction and real-time requirements. We report a HT-hardware architecture for road-lane detection with parallelized voting procedure, local maximum algorithm and FPGA-prototype implementation. Parallelization of the global design is realized on the basis of θ-value discretization in the Hough space. Four major hardware modules are developed for edge detection in the original video frames, computation of the characteristic edge-pixel values (ρ,θ) in Hough-space, voting procedure for each (ρ,θ) pair with parallel local-maximum-based peak voting-point extraction in Hough space to determine the detected straight lines. Implementation of a prototype system for real-time road-lane detection on a low-cost DE1 platform with a Cyclone II FPGA device was verified to be possible. An average detection speed of 135 frames/s for VGA (640x480)-frames was achieved at 50 MHz working frequency.