Vehicle Logo Recognition Using a SIFT-Based Enhanced Matching Scheme
Vehicle Logo Recognition Using a SIFT-Based Enhanced Matching Scheme
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DOI：
10.1109/tits.2010.2042714
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发表时间：
2010-06-01
影响因子：
8.5
通讯作者：
Kayafas, Eleftherios
中科院分区：
文献类型：
--
作者：
Psyllos, Apostolos P.;Anagnostopoulos, Christos-Nikolaos E.;Kayafas, Eleftherios
提出了一种基于改进的尺度不变特征变换(SIFT)特征匹配的车标识别算法。该算法在一组1200个标识图像上进行了评估，这些图像来自十家不同的汽车制造商。进行了一系列的实验，将1200幅图像分别分割成训练集和测试集。实验结果表明，与标准的基于SIFT的特征匹配方法相比，本文提出的改进匹配方法提高了识别精度。结果表明，车标识别率高，处理时间短，适合于实时应用。
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.