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Simplified Neural Networks with Smart Detection for Road Traffic Sign Recognition

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Advances in Information and Communication (FICC 2019)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 69))

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Abstract

Improving driver’s safety is the main goal of the advanced driver assistance system, which has been widely deployed for proactive driving security in recent years. For road driving, the advanced driver assistance system should visually recognize circular prohibition and triangular warning traffic signs to help drivers to grab complete traffic conditions. In this paper, we proposed a low-computation neural assistance system for traffic sign recognition. First, we proposed shaped-based detection algorithms to detect the regions, which are with circle and triangular traffic signs in designated regions of interest. For classification to those detected regions, we then suggest a convolutional neural network to achieve about 5% improvement of top 1 accuracy compared with LeNet model in German traffic sign recognition benchmarks dataset. For real applications, we also establish a Taiwanese traffic sign database to train the proposed neural network. The simulation results on self-collect driving videos demonstrate that the proposed traffic sign recognition system achieved above 97% recognition rate can be effectively adopted in ADAS applications.

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Acknowledgements

This work was supported by the Ministry of Science and Technology, Taiwan, under Grant MOST 105-2221-E-006-065-MY3.

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Authors and Affiliations

  1. Department of Electrical Engineering, Institute of Computer and Communication Engineering, National Cheng Kung University, Tainan, Taiwan

    Wei-Jong Yang, Chia-Chun Luo, Pau-Choo Chung & Jar-Ferr Yang

Authors
  1. Wei-Jong Yang
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  2. Chia-Chun Luo
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  3. Pau-Choo Chung
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  4. Jar-Ferr Yang
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Corresponding author

Correspondence to Jar-Ferr Yang .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, UK

    Rahul Bhatia

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Yang, WJ., Luo, CC., Chung, PC., Yang, JF. (2020). Simplified Neural Networks with Smart Detection for Road Traffic Sign Recognition. In: Arai, K., Bhatia, R. (eds) Advances in Information and Communication. FICC 2019. Lecture Notes in Networks and Systems, vol 69. Springer, Cham. https://doi.org/10.1007/978-3-030-12388-8_17

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