INDUCTANCE-PATTERN RECOGNITION FOR VEHICLE RE-IDENTIFICATION
This research attempts to improve the accuracy of vehicle re-identification at successive loop detector stations through improving the distance measures in the pattern matching process. Vehicle inductance-signature data, collected by a California team of researchers, were further analysed at the University of Toronto. Several new distance measures were used to match the normalised waveforms that proved to be outperforming previous features. Other approaches such as horizontal shifting of the waveforms for warping-reduction and Back Propagation Neural Network were also investigated.
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Supplemental Notes:
- Full conference proceedings available on CD-ROM.
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Corporate Authors:
1100 17th Street, NW, 12th Floor
Washington, DC United States 20036 -
Authors:
- Tabib, S M
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Conference:
- 8th World Congress on Intelligent Transport Systems
- Location: Sydney, Australia
- Date: 2001-9-30 to 2001-10-4
- Publication Date: 2001
Language
- English
Media Info
- Features: Figures; References; Tables;
- Pagination: 15p
Subject/Index Terms
- TRT Terms: Automatic vehicle identification; Inductance; Loop detectors; Neural networks; Pattern recognition systems; Waveform analysis
- Subject Areas: Highways; Operations and Traffic Management; I73: Traffic Control;
Filing Info
- Accession Number: 00964257
- Record Type: Publication
- Files: TRIS
- Created Date: Oct 31 2003 12:00AM