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Linux Embedded System for Vehicle License Plates Recognition

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
Josué Batista Mota, Renata Imaculada Soares Pereira, Sandro César Silveira Jucá
10.5120/ijca2018917687

Josué Batista Mota, Renata Imaculada Soares Pereira and Sandro César Silveira Jucá. Linux Embedded System for Vehicle License Plates Recognition. International Journal of Computer Applications 182(9):43-46, August 2018. BibTeX

@article{10.5120/ijca2018917687,
	author = {Josué Batista Mota and Renata Imaculada Soares Pereira and Sandro César Silveira Jucá},
	title = {Linux Embedded System for Vehicle License Plates Recognition},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2018},
	volume = {182},
	number = {9},
	month = {Aug},
	year = {2018},
	issn = {0975-8887},
	pages = {43-46},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume182/number9/29851-2018917687},
	doi = {10.5120/ijca2018917687},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

This article proposes an embedded system with the purpose of vehicle license plates recognition. For the development of this project, it is used the OpenAlpr library and the Python programming language to implement the recognition of the license plates. For the system development, a Linux embedded system based on the free software Raspbian and the Raspberry Pi platform is selected. A conventional webcam for image recognition is applied. The proposed project hit rate reached around 92%.

References

  1. Mancini, M. 2017. “Internet das Coisas: História, Conceitos, Aplicações e Desafios” Pmi-Sp, p. 9.
  2. Martins, M. A. 2017. “Identificação de placas de trânsito através da classificação de imagens usando redes neurais artificiais,” p. 45.
  3. Nardi, E., Polak L. and Valiati, L. 2015. “Sistema De Controle De Acesso Utilizando Reconhecimento De Caracteres Em Placa De Automóvel”.
  4. Penha, F. J. S. 2013. “Implementação de um sistema de reconhecimento de caracteres em placas de automóveis baseado em Extreme Learning Machine”.
  5. Leite, L., Antonello, R. 2017. “ Identificação automática de placa de veículos através de processamento de imagem e visão computacional”.
  6. Filho, J.F.S.P., Souza, A.C.S. 2014. “Localização de Placas de licenciamento veicular em tempo real utilizando OpenCV com CUDA”.
  7. Hossain Y. and George F. P., “IOT based Automated Intrusion Detection System”. 2018. Vol. 180, no. 35, pp. 56–61.
  8. RPi Foundation. 2016. Raspberry Pi - Teach, Learn, and Make with Raspberry Pi. [Online]. Avaiable at: https://www.raspberrypi.org/.
  9. Rayaji S., “3D Image Reconstruction using Raspberry Pi”. 2018. Vol. 181, no. 4, pp. 8–13.
  10. Sony Entertainment Network, “PlayStation Eye,” 2007.
  11. Ylonen T., “The Secure Shell (SSH) Connection Protocol,” 2006.
  12. Hill M., “OpenAlpr”. 2018. [Online]. Avaiable at: https://github.com/matthill.

Keywords

Raspberry Pi, OpenAlpr, vehicle license plates.