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Speed Limit Road Sign Detection and Recognition System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 131 - Number 2 |
| Year of Publication: 2015 |
| Authors: Fakhradeen Hamid Ali, Mohammad Haqqi Ismail |
10.5120/ijca2015907275
|
Fakhradeen Hamid Ali, Mohammad Haqqi Ismail . Speed Limit Road Sign Detection and Recognition System. International Journal of Computer Applications. 131, 2 ( December 2015), 43-50. DOI=10.5120/ijca2015907275
Abstract
Traffic signs in general and speed limit signs in particular are considered one of the most important means of traffic safety, and the aim of the current research is to design a system that detects and recognizes speed limit sign with high accuracy and high processing speed. At the beginning, red color objects are detected from the image and after finding the red color signs the circle is determined using Hough’s transform then from inside the circle, the numeric part from the circle image is extracted. Digital circle images are segmented to extract the number alone, and then these numbers are recognized by a trained neural network. Neural network achieved a success rate in recognition reached to 98.9%. Parallel programming concept is used to reduce the execution time using OpenMP and OpenCl programming. The study showed that the total execution speed according to the designed scheme to run the speed limit sign detection and recognition by using a mix of central processing unit with multi cores and graphics processing unit is 65 frames/sec for complete images and 90 frames/sec when cropping the effective part from the total size of the image. Recognition system is capable of recognizing the sign even if the vehicle speed exceeds 120 km/h.
References
- Torresen,J., J. W. Bakke and L. Sekanina., 2004. Efficient recognition of speed limit signs. In Intelligent Transportation Systems, Washington, D.C.,USA. Proceedings. The 7th International IEEE Conference on, pp. 652-656.
- Fleyeh, H. 2005.Traffic signs color detection and segmentation in poor light conditions. MVA2005 IAPR Conference on Machine VIsion Applications,Tsukuba Science City, Japan.
- Ishak K. A., 2006. A Speed limits Sign Recognition System Using Artificial Neural Network. in Research and Development, MALAYSIA, pp. 127-131.
- Zakir, U.,A.N.J.Leonce, and E.A.Edirisinghe, 2010. Road sign segmentation based on colour spaces: a comparative study. Proceedings of the 11th IASTED International Conference Computer Graphics and Imaging (CGIM), Innsbruck, Austria.
- Thouti,K.and S.R.Sathe, 2012. Comparison of OpenMP & OpenCL parallel processing technologies. (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 3, No.4.
- Dore, A., and S. Lasrado, 2014. Performance analysis of Soble edge filter on heterogeneous system using OpenCL. IJRET: International Journal of Research in Engineering and Technology, Volume: 03 Special Issue: 03, Available @ http://www.ijret.org.
- Slabaugh,G. R. Boyes and X. Yang, . Multicore image processing with OpenMP .
- Inc.(AMD), 2010. Introduction to OpenCL™
- Programming. Training guide , publication #: 137-41768-10. Rev: A. Issue.
- Modi,S. , 2011.Automated coin recognition system using ANN. M.Sc. thesis, Thapar University, PATIALA.
- Bedi, A., 2011. A Colour segmentation method for detection of New Zealand speed signs.M.Sc. thesis, School of Engineering, Auckland University of Technology, New Zealand.
- Jamil,N., T. M. T. Sembok2,and Z. Abu Bakar1, 2008. Noise removal and enhancement of binary images using morphological operations.978-1-4244-2328-6/08/$25.00 © IEEE.
- Paul, B., 2011.Informatics simulation &exploration of mobile license plate detection employing infrared, Canny edge detection, binary threshold and control detection for submission in limited light conditions. M.Sc. thesis, Massey University, Albany, New Zealand.
- Yuen H.K., J. Princen, J. Illingworth and J. KittlerA. 1989. Comparative study of Hough transforms methods for circle finding. AVC doi: 10.5244/C.3.29.
- Burke,R. L. Cramer, N. Dupes, and D. McDannald, 2014. Autonomous robotic boat platform. Presentation in Department of Electrical and Computer Engineering, Bradley University.
- Zhang, T. Y. and C. Y. Suen, 1984. A fast parallel algorithm for thinning digital patterns. Research Contributions, Communic',ations of the ACM M, Volume 27 Number 3.
- Damavandi, Y. and K. Mohammadi. 2004. Speed limit traffic sign detection and recognition. Cybernetics and Intelligent Systems, IEEE Conference on, 2:797{802}.
- http://techreport.com/review/23179/review-nvidia-geforce-gt-640-graphics-card.
- http://www.notebookcheck.net/Intel-HD-Graphics4000.-69168.0.html
- Ravishekhar Banger,B.and K. Bhattacharyya, 2013. OpenCL Programming by Example. Packt Publishing Ltd. Birmingham B3 2PB, UK.
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