A Vehicle Logo Recognition Approach Based on Foreground-Background Pixel-Pair Feature

  • Zhenxing Nie
  • Ye YuEmail author
  • Qiang Jin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10092)


Traditional image features combined with different classifiers are widely used in existing vehicle logo recognition methods, which didn’t take into account the rich structure information of vehicle logos. Considering both their gray and structure information, a novel method based on foreground-background pixel pair (FBPP) feature, in which pixels are randomly sampled from foreground-background skeleton areas, is proposed. The pixel pair feature extraction process takes full consideration of vehicle logo structure, which makes this feature distinctive and discriminative. The experiment results show that, compared with methods based on features mainly focused on gray information, the method based on the proposed feature can achieve higher recognition performance. Especially under weak illumination, our method has shown strong robustness.


Vehicle Logo Recognition Foreground-background Pixel pair feature Skeleton area Random sampling 



This work was supported in part by the National Natural Science Foundation of China (Grant No. 61370167, 61305093), the Anhui Provincial Science and Technology Project (Grant No. 1401b042009).


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.VCC Division, School of Computer and InformationHefei University of TechnologyHefeiChina

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