Real-Time Traffic Sign Detection and Recognition using CNN

被引:11
作者
Santos, D. [1 ]
Silva, F. [1 ]
Pereira, D. [1 ]
Almeida, L. [1 ]
Artero, A. [2 ]
Piteri, M. [2 ]
de Albuquerque, V [3 ]
机构
[1] Univ Oeste Paulista Unoeste, Presidente Prudente, SP, Brazil
[2] Univ Estadual Paulista, UNESP, Presidente Prudente, SP, Brazil
[3] Univ Fortaleza Unifor, Fortaleza, Ceara, Brazil
关键词
Computer Vision; Convolutional Neural Network; Region-Based Convolutional Neural Network;
D O I
10.1109/TLA.2020.9082723
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Traffic signs presents on streets and highways have a distinct set of features which may be used to differentiate each one from each other. 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.
引用
收藏
页码:522 / 529
页数:8
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