Vehicle logo recognition using a sift-based enhanced matching scheme

Psyllos, AP; Anagnostopoulos, C-NE; Kayafas, E

dc.contributor.author	Psyllos, AP	en
dc.contributor.author	Anagnostopoulos, C-NE	en
dc.contributor.author	Kayafas, E	en
dc.date.accessioned	2014-03-01T01:34:50Z
dc.date.available	2014-03-01T01:34:50Z
dc.date.issued	2010	en
dc.identifier.issn	1524-9050	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20886
dc.subject	Image matching	en
dc.subject	Manufacturer recognition	en
dc.subject	Vehicles	en
dc.subject.classification	Engineering, Civil	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.classification	Transportation Science & Technology	en
dc.subject.other	Fast processing time	en
dc.subject.other	Feature matching	en
dc.subject.other	In-vehicle	en
dc.subject.other	Manufacturer recognition	en
dc.subject.other	Matching scheme	en
dc.subject.other	Real-time application	en
dc.subject.other	Recognition accuracy	en
dc.subject.other	Recognition rates	en
dc.subject.other	Scale invariant feature transforms	en
dc.subject.other	Training sets	en
dc.subject.other	Vehicle logo recognition	en
dc.subject.other	Vehicle manufacturers	en
dc.subject.other	Image matching	en
dc.subject.other	Vehicles	en
dc.title	Vehicle logo recognition using a sift-based enhanced matching scheme	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TITS.2010.2042714	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TITS.2010.2042714	en
heal.identifier.secondary	5419948	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	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. © 2006 IEEE.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Intelligent Transportation Systems	en
dc.identifier.doi	10.1109/TITS.2010.2042714	en
dc.identifier.isi	ISI:000278538600009	en
dc.identifier.volume	11	en
dc.identifier.issue	2	en
dc.identifier.spage	322	en
dc.identifier.epage	328	en