The Detection and Recognition of Arrow Markings Recognition Based on Monocular Vision
Road information understanding is a necessary task for both intelligent vehicles and driving assistance systems. Previous research mostly focused on the detection of lane position. Other information provided by arrow markings was scarcely mentioned. In this paper, Arrow extraction is carried out by projection histogram on Inverse perspective image and an arrow markings recognition algorithm is presented based on multi-class support vector machines. An improved Haar wavelet feature extraction approach is utilized to describe the feature of arrow markings. In order to guarantee generalization performance, the F-score method is used for feature reduction. The results show that the algorithm can detect and recognize arrow markings effectively, and its robust to occlusion by other vehicles or poor visibility.
Arrows markings detection Projection Histogram SVM feature eztraction feature reduction
Nan Wang Wei Liu Chunmin Zhang Huai Yuan Jiren Liu
Software Center, Northeastern University, Shen Yang, 110004
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
4380-4386
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）