M-SIFT: A new method for Vehicle Logo Recognition
作者： Apostolos Psyllos , Christos-Nikolaos Anagnostopoulos , Eleftherios Kayafas
DOI: 10.1109/ICVES.2012.6294277
关键词:
摘要: In this paper, a new algorithm for Vehicle Logo Recognition is proposed, on the basis of an enhanced Scale Invariant Feature Transform (Merge-SIFT or M-SIFT). The assessed set 1500 logo images that belong to 10 distinctive vehicle manufacturers. A series experiments are conducted, splitting training (database) and testing (query). It shown MSIFT approach, which proposed in boosts recognition accuracy compared standard SIFT method. reported results indicate average 94.6% true rate logos, while processing time remains low (∼0.8sec).
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