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Reseach Article

Computer Vision System to Aid Drivers of Vehicles through Vertical Signaling Traffic

by Elizˆangela De Souza Rebouc¸as, Samuel Luz Gomes, Pedro Pedrosa Rebouc¸as Filho
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 5
Year of Publication: 2015
Authors: Elizˆangela De Souza Rebouc¸as, Samuel Luz Gomes, Pedro Pedrosa Rebouc¸as Filho
10.5120/20144-2289

Elizˆangela De Souza Rebouc¸as, Samuel Luz Gomes, Pedro Pedrosa Rebouc¸as Filho . Computer Vision System to Aid Drivers of Vehicles through Vertical Signaling Traffic. International Journal of Computer Applications. 115, 5 ( April 2015), 1-7. DOI=10.5120/20144-2289

@article{ 10.5120/20144-2289,
author = { Elizˆangela De Souza Rebouc¸as, Samuel Luz Gomes, Pedro Pedrosa Rebouc¸as Filho },
title = { Computer Vision System to Aid Drivers of Vehicles through Vertical Signaling Traffic },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 5 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number5/20144-2289/ },
doi = { 10.5120/20144-2289 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:53:54.650406+05:30
%A Elizˆangela De Souza Rebouc¸as
%A Samuel Luz Gomes
%A Pedro Pedrosa Rebouc¸as Filho
%T Computer Vision System to Aid Drivers of Vehicles through Vertical Signaling Traffic
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 5
%P 1-7
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The constant increase in the number of vehicle, especially in large urban centers, a growing number of accidents caused by the invasion of neighboring groups of drivers, either by inattention, drowsiness, among others. To mitigate the impact of this problem, this paper proposes the Aid System the Driver Vehicle (ASDV), which is based on a system uses computer vision techniques and Digital Image Processing to detect the tracks of markings and through these identify the behavior that the car driver must have to continue in its tracks of movement on the road. Tests are performed on Unix platform and the Android operating system, obtaining the speed 50 fps and 20 fps, respectively. The tests show satisfactory results, achieving 100% accuracy when the tracks are detected. Therefore, we can conclude that the system is promising and shows potential to be used in real applications.

References
  1. A. R. de Alexandria. System of optical recognition of digits to conventional energy meters. Master's thesis, Universidade Federal do Cear, Fortaleza, 2005.
  2. DNIT. Traffic accident statistics. national department of transport infrastructure. National Department of Transport Infrastructure of the Brazil, 2014.
  3. P. P. Rebouc¸as Filho, R. M. Sarmento, Paulo Csar Cortez, A. C. S. BARROS, and VICTOR HUGO C. ALBUQUERQUE. Adaptive crisp active contour method for segmentation and reconstruction of 3d lung structures. Revista Matria (UFRJ), 2015.
  4. C. R. Franco. Identification of the use of seat belts in car drivers through computer vision. Master's thesis, UNIVALI, Itaja, 2013.
  5. S. L. Gomes, E. S. Rebouc¸as, and P. P. Rebouc¸as Filho. Reconhecimento optico de caracteres para reconhecimento das sinalizac¸ ˜oes verticais das vias de trˆansito. Revista SODEBRAS, 9:9–12, 2014.
  6. R. C. Gonzalez and R. E. Woods. Digital Image Processing. Pearson Prentice Hall, New Jersey, 3a edition, 2010.
  7. J. N. Kaftan, A. P. Kiraly, A. Bakai, M. Das, C. L. Novak, and T. Aach. Fuzzy pulmonary vessel segmentation in contrast enhanced ct data. SPIE Proceedings, 2008.
  8. Takeo Kato, Yoshiki Ninomiya, and Ichiro Masaki. Preceding vehicle recognition based on learning from sample images. IEEE International Conference on Intelligent Transportation Systems, 3:252–260, 2002.
  9. H. Erdinc Kocer and K. Kursat Cevik. Artificial neural networks based vehicle license plate recognition. Procedia Computer Science, 3:1033–1037, 2011.
  10. Takashi Nato, Toshihiko Tsukada, Keiichi Yamada, Kazuhiro Kozuka, and Shin Yamamoto. Robust license-plate recognition methos for passing vehicles under outside environment. IEEE Transactions on Vehicular Technology, 49:2309–2319, 2000.
  11. E. Cavalcanti Neto, E. S. Rebouc¸as, J. L. Moraes, S. L. Gomes, and P. P. Rebouc¸as Filho. Development control parking access using techniques digital image processing and applied computational intelligence. IEEE Transactions on Latin America, 13:272–276, 2015.
  12. F. M. Peixoto, E. S. Rebouc¸as, F. G. L. Xavier, and P. P. Rebouc¸as Filho. Desenvolvimento de um software para clculo da densidade de ndulos de grafita em ferro fundido nodular atravs de processamento digital de imagens. Revista Matria (UFRJ), 2015.
  13. E. S. Rebouc¸as, R. M. Sarmento, and P. P. Rebouc¸as Filho. 3d adaptive balloon active contour: method of segmentation of structures in three dimensions. Revista IEEE Amrica Latina, 2015.
  14. Norizam Sulaiman, Sri Nor Hafidah Mohammad Jalani, Mahfuzah Mustafa, and Kamarul Hawari. Development of automatic vehicle plate detection system. In IEEE 3rd International Conference on System Engineering and Technology, 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Vertical traffic signs traffic lines Digital Image Processing Computer Vision System Aid to the car driver.