TY - GEN
T1 - Geometrical, physical and text/symbol analysis based approach of traffic sign detection system
AU - Liu, Yangxing
AU - Ikenaga, Takeshi
AU - Goto, Satoshi
PY - 2006/12/1
Y1 - 2006/12/1
N2 - Traffic sign detection is a valuable part of future driver support system. In this paper, we present a novel framework to accurately detect traffic signs from a single color image by analyzing geometrical, physical andtext/symbol features of traffic signs. First, we utilize an elaborate edge detection algorithm to extract edge map and accurate edge pixel gradient information. Second 2-D geometric primitives (circles, ellipses, rectangles and triangles) are quickly extracted from image edge map. Third the candidate traffic sign regions are selected by analyzing the intrinsic color features, which are invariant to different illumination conditions, of each region circumvented by geometric primitives. Finally a text and symbol detection algorithm is introduced to classify true traffic signs. Experimental results demonstrated the capabilities of our algorithm to detect traffic signs with respect to different size, shape, color and illumination conditions.
AB - Traffic sign detection is a valuable part of future driver support system. In this paper, we present a novel framework to accurately detect traffic signs from a single color image by analyzing geometrical, physical andtext/symbol features of traffic signs. First, we utilize an elaborate edge detection algorithm to extract edge map and accurate edge pixel gradient information. Second 2-D geometric primitives (circles, ellipses, rectangles and triangles) are quickly extracted from image edge map. Third the candidate traffic sign regions are selected by analyzing the intrinsic color features, which are invariant to different illumination conditions, of each region circumvented by geometric primitives. Finally a text and symbol detection algorithm is introduced to classify true traffic signs. Experimental results demonstrated the capabilities of our algorithm to detect traffic signs with respect to different size, shape, color and illumination conditions.
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M3 - Conference contribution
AN - SCOPUS:34547332003
SN - 490112286X
SN - 9784901122863
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 238
EP - 243
BT - 2006 IEEE Intelligent Vehicles Symposium, IV 2006
T2 - 2006 IEEE Intelligent Vehicles Symposium, IV 2006
Y2 - 13 June 2006 through 15 June 2006
ER -