TY - GEN
T1 - Lane detection of multi-visual-features fusion based on D-S theory
AU - Chen, Chao
AU - Wang, Junzheng
AU - Chang, Huayao
AU - Li, Jing
PY - 2011
Y1 - 2011
N2 - A novel lane detection algorithm based on multi-visual-features fusion by using D-S evidence theory is introduced to improve the robustness against illumination variations, shadows and road surface cracks, etc. First, the gradient magnitude, gradient direction, hue and value detection operators are chosen to construct the evidence bodies, for which the basic probability assignment functions are designed respectively. Then, after the pretreatment of conflict focal elements, the evidences are combined to obtain the weights of each pixel as lane candidate points according to the maximum reliability criterion. Finally, the parameters of piecewise linear lane model are calculated by weighted Hough transform with constraint and KF is used for lane tracking. The experimental results show that this method can achieve higher reliability and adaptability for lane detection than the algorithm simply using the edge or color feature, and satisfies the real-time requirement for navigation.
AB - A novel lane detection algorithm based on multi-visual-features fusion by using D-S evidence theory is introduced to improve the robustness against illumination variations, shadows and road surface cracks, etc. First, the gradient magnitude, gradient direction, hue and value detection operators are chosen to construct the evidence bodies, for which the basic probability assignment functions are designed respectively. Then, after the pretreatment of conflict focal elements, the evidences are combined to obtain the weights of each pixel as lane candidate points according to the maximum reliability criterion. Finally, the parameters of piecewise linear lane model are calculated by weighted Hough transform with constraint and KF is used for lane tracking. The experimental results show that this method can achieve higher reliability and adaptability for lane detection than the algorithm simply using the edge or color feature, and satisfies the real-time requirement for navigation.
KW - D-S Evidence Theory
KW - Lane Detection
KW - Multi-visual-features
UR - http://www.scopus.com/inward/record.url?scp=80053088590&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:80053088590
SN - 9789881725592
T3 - Proceedings of the 30th Chinese Control Conference, CCC 2011
SP - 3047
EP - 3052
BT - Proceedings of the 30th Chinese Control Conference, CCC 2011
T2 - 30th Chinese Control Conference, CCC 2011
Y2 - 22 July 2011 through 24 July 2011
ER -