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Polish Road Signs Detection and Classification System Based on Sign Sketches and ConvNet

  • Łukasz ChechlińskiEmail author
  • Bartłomiej Chechliński
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 644)

Abstract

In this paper, we present a novel approach to detection and classification of road traffic signs. Detection and classification is performed simultaneously by the Deep Convolutional Neural Network, based on the architecture of VGG Net. Classifier is trained with the usage of sign sketches, obtained directly from the Polish Highway Code. All 169 simple signs are used. The system was tested on 100 images obtained from Google Street View. The re-view of related work shows that our system does not reach the state-of-the-art results yet, but it is much easily scalable and adaptable to the new high-way codes.

Keywords

Traffic signs Deep Learning ConvNet Synthetic training base Sign detection 

Notes

Acknowledgement

This work was supported by the WUT Faculty of Mechatronics Dean’s grant no. 504/02806.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Łukasz Chechliński
    • 1
    Email author
  • Bartłomiej Chechliński
    • 2
  1. 1.Faculty of MechatronicsWUTWarsawPoland
  2. 2.Faculty of Mathematics and Information ScienceWUTWarsawPoland

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