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