Traffic Signs Detection Based on Haar-Like Features and Adaboost Classifier
Traffic Signs Detection Based on Haar-Like Features and Adaboost Classifier
- New search for: Li, Zhijiang
- New search for: Dong, Chuan
- New search for: Zheng, Ling
- New search for: Liu, Long
- New search for: Li, Zhijiang
- New search for: Dong, Chuan
- New search for: Zheng, Ling
- New search for: Liu, Long
Traffic sign detection is an important part of the Intelligent Transportation Systems, and the goal is to separate traffic signs from complex natural scenes quickly and accurately. This paper proposes a method based on adaboost classifier for haar-like features and linear discriminant analysis (LDA) to detect the traffic signs. 1980 positive samples and 4017 negative samples were trained in offline status to provide a rough classification of the interested region in image. Finally, LDA was used to determine the category of interested regions of traffic signs. The method mentioned in this paper has been proved to be effective through static tests and unmanned vehicle tests equipped with independent research.
Document information
Traffic Signs Detection Based on Haar-Like Features and Adaboost Classifier
Second International Conference on Transportation Information and Safety ; 2013 ; Wuhan, China
ICTIS 2013 ; 1128-1135
2013-06-11
Conference paper
Electronic Resource
English
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