Vehicle Detection and Recognition in Greyscale Imagery
Vehicle Detection and Recognition in Greyscale Imagery
This paper details a novel two-stage vehicle detection and recognition algorithm by combining an image-processing region of interest (ROI) designator to cue a secondary recognition process implemented using principal component analysis (PCA) as input to a Multi-Layered Perceptron (MLP) classifier. Both the image-processing system and the MLP classifier have been designed for real-time implementation and data-fusion with other information sources.
473--479
Matthews, N.D.
67f2b57f-7b49-47ef-8910-a7bada8af702
An, P.E.
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Charnley, D.
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Harris, C.J.
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April 1996
Matthews, N.D.
67f2b57f-7b49-47ef-8910-a7bada8af702
An, P.E.
5dc94657-d009-4d13-9a0f-6645a9d296d9
Charnley, D.
201a3f46-6348-4188-a8af-9e4e08c5889a
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Matthews, N.D., An, P.E., Charnley, D. and Harris, C.J.
(1996)
Vehicle Detection and Recognition in Greyscale Imagery.
Control Engineering Practice, 4 (4), .
Abstract
This paper details a novel two-stage vehicle detection and recognition algorithm by combining an image-processing region of interest (ROI) designator to cue a secondary recognition process implemented using principal component analysis (PCA) as input to a Multi-Layered Perceptron (MLP) classifier. Both the image-processing system and the MLP classifier have been designed for real-time implementation and data-fusion with other information sources.
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Published date: April 1996
Organisations:
Southampton Wireless Group
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Local EPrints ID: 250108
URI: http://eprints.soton.ac.uk/id/eprint/250108
PURE UUID: 8fc3f162-ae24-4377-a417-77a9d7431488
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Date deposited: 04 May 1999
Last modified: 08 Jan 2022 02:38
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Contributors
Author:
N.D. Matthews
Author:
P.E. An
Author:
D. Charnley
Author:
C.J. Harris
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