Title :
Fast shape-based road sign detection for a driver assistance system
Author :
Loy, Gareth ; Barnes, Nick
Author_Institution :
Comput. Vision & Active Perception Lab., Royal Inst. of Technol., Stockholm, Sweden
fDate :
28 Sept.-2 Oct. 2004
Abstract :
A new method is presented for detecting triangular, square and octagonal road signs efficiently and robustly. The method uses the symmetric nature of these shapes, together with the pattern of edge orientations exhibited by equiangular polygons with a known number of sides, to establish possible shape centroid locations in the image. This approach is invariant to in-plane rotation and returns the location and size of the shape detected. Results on still images show a detection rate of over 95%. The method is efficient enough for real-time applications, such as on-board-vehicle sign detection.
Keywords :
driver information systems; object detection; road vehicles; driver assistance system; road sign detection; shape centroid location; shape detection; Australia; Computer vision; Detectors; Image edge detection; Image segmentation; Pixel; Road safety; Robustness; Shape; Voting;
Conference_Titel :
Intelligent Robots and Systems, 2004. (IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on
Print_ISBN :
0-7803-8463-6
DOI :
10.1109/IROS.2004.1389331