Vehicle Logo Recognition Using a SIFT-Based Enhanced Matching Scheme

被引：143

作者：

Psyllos, Apostolos P. ^{[1
]}

Anagnostopoulos, Christos-Nikolaos E. ^{[2
]}

Kayafas, Eleftherios ^{[1
]}

机构：

[1] Natl Tech Univ Athens, Dept Elect & Comp Engn, Athens 15780, Greece

[2] Univ Aegean, Dept Cultural Technol & Commun, Mitilini 81100, Greece

来源：

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | 2010年 / 11卷 / 02期

关键词：

Image matching; manufacturer recognition; vehicles;

D O I：

10.1109/TITS.2010.2042714

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

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.

引用

页码：322 / 328

页数：7

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