DocumentCode :
479367
Title :
Automatic Vehicle Classification Based on Video with BP Neural Networks
Author :
Li, Xiaobin ; Fu, Hui ; Xu, Jianmin
Author_Institution :
Sch. of Traffic & Commun., South China Univ. of Technol., Guangzhou
fYear :
2008
fDate :
12-14 Oct. 2008
Firstpage :
1
Lastpage :
3
Abstract :
The classification and statistics of the vehicles type in the road section are important parameters for the traffic management and control. The paper put forward the vehicle classification using image invariant moment and BP neural networks. First of all, road background is rebuild according to the serials images, and the background differences are used to segment vehicle region, invariant moment features are extracted for each vehicle region. The invariant moment features of vehicle will be the input of BP neural networks with three layers, and the vehicle type is classified according to the output of the BP neural networks. The test has verified the validity of this method.
Keywords :
backpropagation; feature extraction; image classification; image segmentation; neural nets; traffic engineering computing; video signal processing; BP neural network; automatic vehicle classification; image invariant moment; invariant moment feature extraction; road background; video detection; Automated highways; Automatic control; Calibration; Communication system traffic control; Infrared detectors; Intelligent vehicles; Neural networks; Road vehicles; Statistics; Transportation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-2107-7
Electronic_ISBN :
978-1-4244-2108-4
Type :
conf
DOI :
10.1109/WiCom.2008.3060
Filename :
4681249
Link To Document :
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