Method for Preceding Vehicle Type Classification Based on Sparse Representation

2011 ◽  
Vol 2243 (1) ◽  
pp. 74-80 ◽  
Author(s):  
Yanwen Chong ◽  
Wu Chen ◽  
Zhilin Li ◽  
William H. K. Lam
Keyword(s):  
Sparse Representation ◽  
Vehicle Type ◽  
Preceding Vehicle ◽  
Vehicle Type Classification ◽  
Type Classification

scholarly journals Moroccan Video Intelligent Transport System: Vehicle Type Classification Based on Three-Dimensional and Two-Dimensional Features

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 72528-72537 ◽  
Author(s):  
Hatim Derrouz ◽  
Abderrahim Elbouziady ◽  
Hamd Ait Abdelali ◽  
Rachid Oulad Haj Thami ◽  
Sanaa El Fkihi ◽  
...  
Keyword(s):  
Transport System ◽  
Three Dimensional ◽  
Intelligent Transport System ◽  
Two Dimensional ◽  
Intelligent Transport ◽  
Vehicle Type ◽  
Vehicle Type Classification ◽  
Type Classification

Wavelet Packet Analysis Based Feature Extraction of Vehicular Acoustic Signal

2011 ◽  
Vol 55-57 ◽  
pp. 1593-1598
Author(s):  
Xiao Xuan Qi ◽  
Jian Wei Ji ◽  
Xiao Wei Han ◽  
Zhong Hu Yuan
Keyword(s):  
Acoustic Signal ◽  
Rbf Neural Network ◽  
Wavelet Packet ◽  
Wavelet Packet Analysis ◽  
Moving Vehicle ◽  
Time Frequency ◽  
Vehicle Type ◽  
Feature Information ◽  
Vehicle Type Classification ◽  
Type Classification

In this paper, an approach based on wavelet packet analysis is proposed to deal with the problem that acoustic signal of moving vehicle is easily influenced by environmental noise in vehicle type classification. Wavelet packet analysis is applied to extract local and detail feature information of acoustic signal in the time-frequency domain. Firstly, raw acoustic signal is decomposed into different frequency bands by wavelet packet analysis, and then decomposition coefficients are reconstructed. The energy of every frequency band component is used to form the feature vector. Finally, vehicle type classification is implemented by RBF neural network on the basis of these feature vectors. Experimental results show that the proposed method is feasible and effective.

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