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

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Transactions on Edutainment XIII

Part of the book series: Lecture Notes in Computer Science ((TEDUTAIN,volume 10092))

Abstract

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.

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Acknowledgment

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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Authors and Affiliations

  1. VCC Division, School of Computer and Information, Hefei University of Technology, Hefei, 230009, China

    Zhenxing Nie, Ye Yu & Qiang Jin

Authors
  1. Zhenxing Nie
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  2. Ye Yu
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  3. Qiang Jin
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Corresponding author

Correspondence to Ye Yu .

Editor information

Editors and Affiliations

  1. Hangzhou Normal University, Hangzhou, China

    Zhigeng Pan

  2. Graduate School of Media Design, Keio University, Yokohama-shi, Kanagawa, Japan

    Adrian David Cheok

  3. University of Education, Weingarten, Germany

    Wolfgang Müller

  4. Zhejiang University, Zhejiang, China

    Mingmin Zhang

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Nie, Z., Yu, Y., Jin, Q. (2017). A Vehicle Logo Recognition Approach Based on Foreground-Background Pixel-Pair Feature. In: Pan, Z., Cheok, A., Müller, W., Zhang, M. (eds) Transactions on Edutainment XIII. Lecture Notes in Computer Science(), vol 10092. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54395-5_18

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  • DOI: https://doi.org/10.1007/978-3-662-54395-5_18

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-54394-8

  • Online ISBN: 978-3-662-54395-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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