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Recognition of Natural Road Sign Based on the Improved Curvature Feature

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 727))

Abstract

To solve the recognition of road sign with an intelligent vehicle in vision-based navigation, road sign extraction and matching techniques required in outdoor scene was proposed in this paper. The method of the improved curvature based on feature extraction and binary description took the advantage of reasonable features distribution to overcome the problems of traditional features uneven distribution. Binary description method was represented to solve the real-time problem of feature matching. Through the validity and real-time performance of different algorithms are compared by experiments and indicate that the method can not only overcome negative influences from the disturb of non-targets, while spending on average only 46 ms processing each frame, but also meet the requirements of robustness, real-time, and accuracy.

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References

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Acknowledgment

This work has been supported by the Jiangsu Engineering Research Center for Networking of Elementary Education Resources (grantnumber: BM2013123).

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Correspondence to Yanqing Wang .

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© 2017 Springer Nature Singapore Pte Ltd.

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Wang, Y., Zheng, H., Chen, W. (2017). Recognition of Natural Road Sign Based on the Improved Curvature Feature. In: Zou, B., Li, M., Wang, H., Song, X., Xie, W., Lu, Z. (eds) Data Science. ICPCSEE 2017. Communications in Computer and Information Science, vol 727. Springer, Singapore. https://doi.org/10.1007/978-981-10-6385-5_57

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  • DOI: https://doi.org/10.1007/978-981-10-6385-5_57

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6384-8

  • Online ISBN: 978-981-10-6385-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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