DocumentCode :
1566401
Title :
Automatic vehicle classification instrument based on multiple sensor information fusion
Author :
Liu, Weiming ; Zhao, Xueping ; Xiao, Jingfang ; Wu, Youlong
Author_Institution :
Sch. of Traffic & Transp. Eng., Central South Univ., Changsha, China
Volume :
1
fYear :
2005
Firstpage :
379
Abstract :
This paper presents a kind of automatic vehicle classification (AVC) instrument for expressway toll collection system based on multiple sensor information fusion technique according to the complicated characteristics of vehicle types in China, In order to develop the instrument, we make use of the video detection segregator, infrared detection technique, piezomagnetic sensor, multiple sensor information fusion technique based on BP neural network. The training result is obtained by 1500 training samples and the training accuracy rate is up to 99.4%. And the simulation accuracy rate on 500 samples is up to 99.2%. The results show that the classification precision is high and the instrument has great value to be popularized.
Keywords :
image classification; neural nets; object detection; road vehicles; sensor fusion; video signal processing; AVC instrument; BP neural network; China vehicle type; automatic vehicle classification; classification precision; expressway toll collection system; infrared detection; multiple sensor information fusion; piezomagnetic sensor; simulation accuracy rate; training accuracy rate; training sample; video detection segregator; Automatic voltage control; Axles; Infrared detectors; Infrared sensors; Instruments; Sensor fusion; Sensor phenomena and characterization; Thin film sensors; Vehicles; Wheels; AVC; ETC; Multiple Sensor Information Fusion; Neural Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology and Applications, 2005. ICITA 2005. Third International Conference on
Print_ISBN :
0-7695-2316-1
Type :
conf
DOI :
10.1109/ICITA.2005.82
Filename :
1488831
Link To Document :
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