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An Overview of Traffic Signs Recognition Methods

by Prachi Dewan, Rekha Vig, Neeraj Shukla, B. K. Das
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 168 - Number 11
Year of Publication: 2017
Authors: Prachi Dewan, Rekha Vig, Neeraj Shukla, B. K. Das
10.5120/ijca2017914524

Prachi Dewan, Rekha Vig, Neeraj Shukla, B. K. Das . An Overview of Traffic Signs Recognition Methods. International Journal of Computer Applications. 168, 11 ( Jun 2017), 7-11. DOI=10.5120/ijca2017914524

@article{ 10.5120/ijca2017914524,
author = { Prachi Dewan, Rekha Vig, Neeraj Shukla, B. K. Das },
title = { An Overview of Traffic Signs Recognition Methods },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2017 },
volume = { 168 },
number = { 11 },
month = { Jun },
year = { 2017 },
issn = { 0975-8887 },
pages = { 7-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume168/number11/27917-2017914524/ },
doi = { 10.5120/ijca2017914524 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:15:50.654584+05:30
%A Prachi Dewan
%A Rekha Vig
%A Neeraj Shukla
%A B. K. Das
%T An Overview of Traffic Signs Recognition Methods
%J International Journal of Computer Applications
%@ 0975-8887
%V 168
%N 11
%P 7-11
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image processing has many areas of applications like in metrological prediction of weather conditions, medical science, artificial intelligence, robotics etc. Traffic signs recognition system is in fact the most happening area of research these days. As the world is moving towards the driverless vehicles, a more automated world is the utmost requirement for improving the road safety. Such systems can help the drivers on signs that they may not have noticed beforehand. These systems are so designed so that they consume less power and hence can be efficiently implemented on hardware. FPGA’s are preferred over CPU and GPU due to its low cost and power, prototyping applications and next levels to ASIC’s development. In this paper we have quoted some basic challenges in traffic signs recognition methods and summarized the various detection and recognition techniques for traffic signs. This paper divided the various methods into three categories: color-based, shape-based and learning- based. We have concluded that the Xilinx System Generator is the best tool while implementing on FPGA’s. It is the fastest resource estimation tool in order to take full advantage of FPGA’s resources. Finally, the hardware perspective of traffic signs implementation is briefly examined.

References
  1. Stefano Marsi, Gaetano Impoco, Anna Ukovich, Sergio Carrato and Giovanni Ramponi,” Video Enhancement and Dynamic Range Control of HDR Sequences for Automotive Applications”, EURASIP Journal on Advances in Signal Processing, Vol.2007 Article ID 80971.
  2. Arturo Escalera, Lius Moreno, Miguel Salichs and Jose Armingol,”Road traffic Sign Detection and Classification”, IEEE Transactions on Industrial Electronics, Vol.44, No.6 , pp.848-859, December 1997.
  3. Sheldon Waite and Erdal Oruklu,” FPGA-Based Traffic Sign Recognition for Advanced Driver Assistance Systems”, Journal of Transportation Technologies, Vol.3, pp.1-16, November 2012.
  4. Chokri Souani, Hassene Faiedh and Kamel Besbes ,” Efficient algorithm for automatic road sign recognition and its hardware implementation”, Journal of Real Time Image Processing, Vol.9, pp.79–93,April 2013.
  5. Karla Brkic,"An overview of traffic sign detection methods”, Department of Electronics, Microelectronics, Computer and Intelligent Systems Faculty of Electrical Engineering and Computing Unska, 2010.
  6. Ching-Hao Lai and Chia-Chen Yu, "An efficient real-time traffic sign recognition system for intelligent vehicles with smart phones", In Technologies and Applications of Artificial Intelligence (TAAI), 2010 IEEE International Conference , pp. 195-202, 2010.
  7. C.Y.Fang, S.W Chen and C.S. Fuh,” Road sign detection and tracking”, IEEE Transactions on Vehicular Technology, Vol. 52, No. 5, pp. 1329–1341.September 2003.
  8. Arturo Escalera, Luis E. Moreno, Miguel Angel Salichs and José Maria Armingol " Road traffic sign detection and classification" ,IEEE transactions on Industrial Electronics , Vol. 44, No. 6, pp. 848-859,December 1997.
  9. Ching- Hao Lai, and Yu Chia-Chen "An efficient real-time traffic sign recognition system for intelligent vehicles with smart phones", In IEEE International Conference on Technologies and Applications of Artificial Intelligence (TAAI), pp. 195-202, 2010.
  10. M. Benallal and J. Meunier,”Real-time color segmentation of road signs”, IEEE Canadian Conference on Electrical and Computer Engineering, Vol.3, pp.1823-1826,2003.
  11. E. Oruklu, D. Pesty, J. Neveux and J. E .Guebey ,” Real Time Traffic Sign Detection and Recognition for in car Driver Assistance Systems”, IEEE International Symposium on Circuits and System, pp.976-979,2012.
  12. Y. Aoyagi and T. Asakura ,“ A study on traffic sign recognition in scene image using genetic algorithm and neural networks”, IEEE International Conference on Industrial Electronics, Control and Instrumentation ,Vol. 3, pp. 1838-1843,1996.
  13. H.G.Moreno , S.M.Bascón , P.G.Jiménez.and S.F.Arroyo,” Goal Evaluation of Segmentation Algorithms for Traffic Sign Recognition”, IEEE Transaction on Intelligent Transportation Systems, Vol. 11, No. 4, pp.917- 930,2010.
  14. Claus Bahlmann, Ying Zhu, Ramesh Visvanathan, M. Pellkofer and K.Thorsten,” A system for Traffic Sign detection ,tracking and recognition Using color, shape and motion Information”, In IEEE proceedings of Intelligent Vehicles Symposium, pp. 255-260,2005.
  15. 15] Miguel Angel García-Garrido, Miguel Angel Sotelo and Ernesto Martin- Gorostiza,” Fast traffic sign detection and recognition under changing lighting conditions”, In IEEE Intelligent Transportation Systems Conference, pp. 811-816, 2006.
  16. Anh-Tuan Hoang, Tetsush Koide and Masaharu Yamamoto,” Low Cost Hardware Implementation for Traffic Sign Detection system”, IEEE Asia Pacific Conference on Circuit and System, pp.363-366, 2014.
  17. Aurore Arlicot,Bahman Soheilian and Nicolas Paparoditis,” Circular road sign extraction from street level images using color, shape and texture databases maps”, Titled in International Archives of Photogrammetry, Remote Sensing and Spatial Informational services in IAPRS,Vol.38, pp. 205-210, 2009.
  18. Fabien Moutarde, Alexandre Bargeton, Anne Herbin and Lowik Chanussot,” Robust on-vehicle real-time visual detection of American and European speed limit signs with a modular Traffic Signs Recognition system”, In IEEE Intelligent Vehicles Symposium, Istanbul, Turkey, pp.1122- 1126,June 2007.
  19. De La Escalera, J. Ma Armingol and Mario Mata, Traffic Sign Recognition and Analysis for intelligent vehicles”, Journal of image and vision computing, Vol.21, No.3, pp.247-258, 2003.
  20. S.Waite and E. Oruklu,” FPGA-Based Traffic Sign Recognition for Advanced Driver Assistance Systems”, Journal of Transportation Technologies, Vol.3, pp.1-16,2013
  21. J.Greenhalgh and M. Mehdi,” Real-Time Detection and recognition of road traffic signs”, IEEE Transactions on intelligent transportation systems, Vol.13, No.4, pp.1498-1506, 2012
  22. Par Karem and Oguz Tosun,” Real-time traffic sign recognition with map fusion on multicore/many core architectures”, In Acta Polytechnica Hungarica, Vol.9, No.2, pp.231-250, 2012.
  23. A. Karunalithika,R.P.Jayasundra,M.A.Rasamjan ,D.N. Senayanke and V.N.Vithana,” Road sign identification application using image processing and augmented reality”, International journal of advanced computer technology ,Vol. 4,Issue.11.pp.79-93,2015.
  24. Rihab Hamida, Abdessalam Abdelali and Abdellatif Mtibaa,” Hardware implementation and validation of a traffic road sign detection and identification system”, Journal of Real Time Image processing, pp. 1-18, 2016
Index Terms

Computer Science
Information Sciences

Keywords

Traffic Sign Recognition method Field programmable gate array (FPGA) Xilinx system generator (XSG) Advanced Driver assistance system (ADAS) Machine learning techniques.

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