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Vehicle classification based on soft computing algorithms

Abstract

Experiments and results regarding vehicle type classification are presented. Three classes of vehicles are recognized: sedans, vans and trucks. The system uses a non-calibrated traffic camera, therefore no direct vehicle dimensions are used. Various vehicle descriptors are tested, including those based on vehicle mask only and those based on vehicle images. The latter ones employ Speeded Up Robust Features (SURF) and gradient images convolved with Gabor filters. Vehicle type is recognized with various classifiers: artificial neural network, K-nearest neighbors algorithm, decision tree and random forest.

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Category:
Articles
Type:
artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
Published in:
LECTURE NOTES IN COMPUTER SCIENCE pages 70 - 79,
ISSN: 0302-9743
Language:
English
Publication year:
2010
Bibliographic description:
Dalka P., Czyżewski A.: Vehicle classification based on soft computing algorithms// LECTURE NOTES IN ARTIFICIAL INTELLIGENCE. -., nr. Nr 6086 (2010), s.70-79
DOI:
Digital Object Identifier (open in new tab) 10.1007/978-3-642-13529-3_9
Verified by:
Gdańsk University of Technology

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