Real-Time Traffic Sign Detection and Recognition using CNN

Authors

  • Francisco Assis da Silva Unoeste
  • Daniel Castriani Santos
  • Danillo Roberto Pereira
  • Leandro Luiz de Almeida
  • Almir Olivette Artero
  • Marco Antônio Piteri
  • Victor Hugo C. de Albuquerque

Keywords:

Computer Vision, Convolutional Neural Network, Region-Based Convolutional Neural Network

Abstract

Traffic signs are on the streets and highways, they have distinct characteristics. These characteristics can be used to differentiate one from the others. We propose in this paper a real-time traffic sign detection and recognition algorithm using neural networks. In order to detect traffic sign we used a Faster R-CNN (Region-Based Convolutional Neural Network), and to classify we used a Convolutional Neural Network using two different architectures. Some factors can make it difficult, such as light, occlusion, blurring, and others. This work can be applied in several areas, such as Advanced Driving Assistant System and autonomous cars.

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Published

2020-04-12

How to Cite

Silva, F. A. da, Santos, D. C., Pereira, D. R., Almeida, L. L. de, Artero, A. O., Piteri, M. A., & Albuquerque, V. H. C. de. (2020). Real-Time Traffic Sign Detection and Recognition using CNN. IEEE Latin America Transactions, 18(3), 522–529. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/680

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