A vision based automated vehicle classification system.

Author(s)
Till, J.
Year
Abstract

Vision based vehicle classification offers substantial advantages compared with traditional vehicle classification systems, which use information from inductive loops, axle counters, Doppler radar and infra red light curtains to classify vehicles. The principal benefits include the ease of installation and maintenance, as well as much greater flexibility, performance and cost effectiveness. This paper details a vision based classification system, which uses image processing and neural network techniques to classify vehicles, looks at the performance of the system, and discusses problems associated with vision systems. (Author/publisher) For the covering entry of this conference, please see ITRD abstract no. E209471.

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Publication

Library number
C 26101 (In: C 26095 CD-ROM) /73 / ITRD E209478
Source

In: ITS - Transforming the future : proceedings of the 8th World Congress on Intelligent Transportation Systems ITS, Sydney, Australia, 30 September - 4 October 2001, 8 p.

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This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.