DocumentCode :
2791953
Title :
The detection and recognition of arrow markings recognition based on monocular vision
Author :
Wang, Nan ; Liu, Wei ; Zhang, Chunmin ; Yuan, Huai ; Liu, Jiren
Author_Institution :
Software Center, Northeastern Univ., Shenyang, China
fYear :
2009
fDate :
17-19 June 2009
Firstpage :
4380
Lastpage :
4386
Abstract :
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 it´s robust to occlusion by other vehicles or poor visibility.
Keywords :
Haar transforms; artificial intelligence; driver information systems; feature extraction; image recognition; road vehicles; support vector machines; F-score method; Haar wavelet feature extraction; arrow extraction; arrow markings recognition; driving assistance systems; feature reduction; intelligent vehicles; inverse perspective image; lane position detection; monocular vision; multiclass support vector machines; projection histogram; road information understanding; Casting; Feature extraction; Filters; Histograms; Intelligent vehicles; Roads; Robustness; Support vector machine classification; Support vector machines; Vehicle detection; Arrows markings detection; Projection Histogram; SVM; feature extraction; feature reduction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
Type :
conf
DOI :
10.1109/CCDC.2009.5192405
Filename :
5192405
Link To Document :
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