Automated vehicle classification system using advanced noise reduction technology

Xiang, Wei and Otto, Colin and Wen, Peng (2008) Automated vehicle classification system using advanced noise reduction technology. In: 1st International Conference on Signal Processing and Communication Systems (ICSPCS 2007), 17-19 Dec 2007, Gold Coast, Australia.

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Abstract

The demand for non-invasive vehicle counting and classifying devices has grown significantly in past decades due to contributing factors from occupational health and safety standards developed by state road authorities. In this paper, we present an automated vehicle classification system based upon the laser sensor technology. The system is capable of classifying vehicles in multi-lane, high speed environments, and requires no apparatus be placed on the carriageway. As opposed to the conventional Fourier-based filtering method, this paper also proposes a novel wavelet-based noise reduction technique to enhance performance.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2008 DSP for Communication Systems. This publication is copyright. It may be reproduced in whole or in part for the purposes of study, research, or review, but is subject to the inclusion of an acknowledgment of the source.
Depositing User: Dr Wei Xiang
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering
Date Deposited: 22 Jan 2008 05:12
Last Modified: 20 Nov 2014 05:18
Uncontrolled Keywords: automated vehicle classification; vehicle classification; vehicle counting; noise reduction technology
Fields of Research (FOR2008): 09 Engineering > 0906 Electrical and Electronic Engineering > 090609 Signal Processing
09 Engineering > 0906 Electrical and Electronic Engineering > 090605 Photodetectors, Optical Sensors and Solar Cells
02 Physical Sciences > 0205 Optical Physics > 020502 Lasers and Quantum Electronics
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
URI: http://eprints.usq.edu.au/id/eprint/3707

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