NDLI: A Novel Vision-based Method for Real-time Extracting Vehicle Flow Information on a Road

Content Provider	IEEE Xplore Digital Library
Author	Jiajia Tan Jian Qiu Zhang Bo Hu Jun He
Copyright Year	2008
Description	Author affiliation: Dept. of E. E., Fudan Univ., Shanghai (Jiajia Tan; Jian Qiu Zhang; Bo Hu)
Abstract	A novel vision-based method for real time extracting vehicle flow information on a road is proposed in this paper. Two new vision parameters, called as the contrast and luminance distortion ones respectively, are defined and employed to extract the vehicle flow information on the road. The analytical results show that the contrast distortion parameter of a video sequence can restrain the effects of the shadow interferences on the vehicle flow measurements, while the luminance distortion parameter is good for real-time background updating and supplement in order to enhance the accuracy of the measurements. In addition, the unsolved problem of the traditional vision-based methods, failing to distinguish two close consecutive vehicles, can be relaxed to a large extent by combining information from such two parameters. The experimental results from the different roads and vehicle flows under the different whether conditions show that the measurement accuracy of the proposed method is 97.27%.
Starting Page	1294
Ending Page	1299
File Size	839538
Page Count	6
File Format	PDF
ISBN	9781424415403
ISSN	10915281
DOI	10.1109/IMTC.2008.4547242
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-12
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Road vehicles Traffic control Distortion measurement Interference Fluid flow measurement Intelligent transportation systems Vehicle detection Cameras Instrumentation and measurement real-time background updating Contrast distortion luminance distortion shadow interference the consecutive problem
Content Type	Text
Resource Type	Article
Subject	Instrumentation Electrical and Electronic Engineering

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