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Vehicle Logo Recognition Using a SIFT-Based Enhanced Matching Scheme

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3 Author(s)
Apostolos P. Psyllos ; Department of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece ; Christos-Nikolaos E. Anagnostopoulos ; Eleftherios Kayafas

In this paper, a new algorithm for vehicle logo recognition on the basis of an enhanced scale-invariant feature transform (SIFT)-based feature-matching scheme is proposed. This algorithm is assessed on a set of 1200 logo images that belong to ten distinctive vehicle manufacturers. A series of experiments are conducted, splitting the 1200 images to a training set and a testing set, respectively. It is shown that the enhanced matching approach proposed in this paper boosts the recognition accuracy compared with the standard SIFT-based feature-matching method. The reported results indicate a high recognition rate in vehicle logos and a fast processing time, making it suitable for real-time applications.

Published in:

IEEE Transactions on Intelligent Transportation Systems  (Volume:11 ,  Issue: 2 )