吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (1): 271-276.doi: 10.13229/j.cnki.jdxbgxb201601041

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Detection method of vehicle in highway green toll lane based on multi-feature fusion

ZHANG Hao1, 2, LIU Hai-ming1, 2, WU Chun-guo1, 2, ZHANG Yan-mei1, 2, ZHAO Tian-ming1, 2, LI Shou-tao3   

  1. 1.College of Computer Science and Technology, Jilin University, Changchun 130012, China;
    2.Symbol Computation and Knowledge Engineering of Ministry of Education,Jilin University,Changchun 130012, China;
    3.College of Communication Engineering, Jilin University, Changchun 130022, China
  • Received:2014-04-09 Online:2016-01-30 Published:2016-01-30

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Abstract:

In order to ensure efficient computerized detection of vehicles passing green toll lane of highway, a detection method, named PGM-OCSVM, is proposed for free toll lane of highway based on multi-feature fusion. First, the Principal Component Analysis (PCA) is used to filter and simplify the sample characteristics. Then, the Genetic Algorithm is applied for adaptive adjustment of bandwidth of kernel function (σ) and false acceptance rate (v), which are two important parameters of one-class SVM. Finally, a one-class SVM model is constructed to learn the samples and classify the results. Big data analysis demonstrates that the proposed PGM-OCSVM can effectively complete green-vehicle discrimination task. This method has been applied to the vehicle detection system in free toll lane of highway.

Key words: computer applications, SVM, multi-feature fusion, one class classifier, vehicle detection of the free toll lane

CLC Number: 

  • TP391.4
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