Call for Paper - January 2023 Edition
IJCA solicits original research papers for the January 2023 Edition. Last date of manuscript submission is December 20, 2022. Read More

Detection and Recognition of Road Traffic Signs - A Survey

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Sumi K. M., Arun Kumar M. N.
10.5120/ijca2017913038

Sumi K M. and Arun Kumar M N.. Detection and Recognition of Road Traffic Signs - A Survey. International Journal of Computer Applications 160(3):1-5, February 2017. BibTeX

@article{10.5120/ijca2017913038,
	author = {Sumi K. M. and Arun Kumar M. N.},
	title = {Detection and Recognition of Road Traffic Signs - A Survey},
	journal = {International Journal of Computer Applications},
	issue_date = {February 2017},
	volume = {160},
	number = {3},
	month = {Feb},
	year = {2017},
	issn = {0975-8887},
	pages = {1-5},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume160/number3/27050-2017913038},
	doi = {10.5120/ijca2017913038},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

This paper presents a survey on the detection and recognition of traffic signs which has a number of important application areas that include advanced driver assistance systems, road surveying and autonomous vehicles. This has been thoroughly studied for a long time. But still it remains a challenging problem in computer vision due to the different types and the huge variability of informations present in them. This problem can be divided into two stages; first stage will be detection of region that cantains traffic sign candidates and second will be character recognition. For the detection and recognition of text and sign from traffic boards, appropriate methods must be applied to obtain accuracy. This method can be achieved by doing a survey on different methods used to detect and recognize text and signs from traffic boards. In this paper, various techniques for the detection and recognition of traffic signs are explained. A comparitive study is performed on these techniques and their performance is explained.

References

  1. Dilip Singh Solanki, Dr. Gireesh Dixit, “Traffic Sign Detection and Recognition Using Feature Based and OCR Method, ”in Proc. IJRSET vol. 2, no. 2, pp. 32-40, 2002
  2. Chiung-Yao Fang, Sei-Wang Chen, Chiou-Shann Fuh, “Road Sign Detection and Tracking, ”IEEE Trans. Veh. Tech., vol. 52, no. 5, pp. 264-278, Sep. 2003.
  3. W. Wu, X. Chen, and J. Yang, “Detection of text on road signs from video,”IEEE Trans. Intell. Transp. Syst., vol. 6, no. 4, pp. 378-390, Dec. 2005.
  4. A. Reina, R. Sastre, S. Arroyo, and P. Jimenez, “Adaptive traffic road sign panels text extraction,”in Proc. WSEAS ICSPRA, 2006, pp. 295-300.
  5. S. Maldonado-Bascon, S. Lafuente-Arroyo, P. Gil-Jimenez, H. Gomez-Moreno, and F. Lopez-Ferreras, “Road-sign detection and recognition based on support vector machines, ”IEEE Trans. Intell. Transp. Syst., vol. 8, no. 2, pp. 264-278, Jun. 2007.
  6. J. Greenhalgh and M. Mirmehdi, “Traffic sign recognition using MSER and random forests, ”in Proc. EUSIPCO, Aug. 2012, pp. 1935-1939.
  7. J. Greenhalgh and M. Mirmehdi, “Real-time detection and recognition of road traffic signs, ”IEEE Trans. Intell. Transp. Syst., vol. 13, no. 4, pp. 1498-1506, Dec. 2012.
  8. F. Zaklouta and B. Stanciulescu, “Real-time traffic-sign recognition using tree classifiers, ”IEEE Trans. Intell. Transp. Syst., vol. 13, no. 4, pp. 1507-1514, Dec. 2012.
  9. A. Gonzalez, L. Bergasa, and J. Yebes, “Text detection and recognition on traffic panels from street-level imagery using visual appearance,”IEEE Trans. Intell. Transp. Syst., vol. 15, no. 1, pp. 228-238, Feb. 2014.
  10. Jack Greenhalgh and Majid Mirmehdi, “Recognizing Text- Based Traffic Signs,”Trans. Intell. Transp. Syst., vol. 16, no. 3, Jun. 2015.
  11. Nadra Ben Romdhane, Hazar Mliki, Mohamed Hammami, “An Improved Traffic Signs Recognition and Tracking Method for Driver Assistance System,”in Proc. ICIS, Jun. 2016, pp. 26- 29.
  12. Yi Yang, Hengliang Luo, Huarong Xu, and Fuchao Wu, “Towards Real-Time Traffic Sign Detection and Classification,” Trans. Intell. Transp. Syst., vol. 17, no. 7, Jul. 2016.
  13. J. Shi and C. Tomasi, “Good features to track,”in Proc. CVPR, 1994, pp. 593-600.
  14. C. Cortes and V. Vapnik, “Support vector networks,”J. Mach. Learn.,vol. 20, no. 3, pp. 273-297, Sep. 1995.
  15. Aparna A. Dalve , Sankirti S. Shiravale, “A Survey on Real Time Text Detection and Recognition from Traffic Panels, ”in Proc. IJRASET, vol. 3, Dec, 2015.

Keywords

Detection, Recognition, Maximally stable extremal region(MSER), Optical Character Recognition(OCR)