Abstract
A real time road sign detection and recognition system can provide an additional level of driver assistance leading to an improved safety to passengers, road users and other vehicles. Such Advanced Driver Assistance Systems (ADAS) can be used to alert a driver about the presence of a road sign by reducing the risky situation during distraction, fatigue and in the presence of poor driving conditions. This paper is divided into two parts: Detection and Recognition. The detection part includes a novel Combined Colour Model (CCM) for the accurate and robust road sign colour segmentation from video stream. It is complemented by a novel approach to road sign recognition which is based on Local Energy based Shape Histogram (LESH). Experimental results and a detailed analysis to prove the effectiveness of the proposed vision system are provided. An accuracy rate of above 97.5% is recorded.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Automatic Road Sign Detection and Recognition, PhD Thesis, Computer Science Loughborough University (2011), http://lboro.academia.edu/usmanzakir/Papers/1587192/Automatic_Road_Sign_Detection_And_Recognition
Zakir, U., Zafar, I., Edirisinghe, A.E.: Road Sign Detection and Recognition by using Local Energy Based Shape Histogram (LESH). International Journal of Image Processing 4(6), 566–582 (2011)
Zakir, U., Edirishinghe, E.A., Hussain, A.: Road Sign Detection and Recognition from Video Stream Using HSV, Contourlet Transform and Local Energy Based Shape Histogram. In: Zhang, H., Hussain, A., Liu, D., Wang, Z. (eds.) BICS 2012. LNCS, vol. 7366, pp. 411–419. Springer, Heidelberg (2012)
Zakir, U., Leonce, J.N.A., Edirisinghe, A.E.: Road sign segmentation based on colour spaces: A Comparative Study. In: Proceedings of the 11th Iasted International Conference on Computer Graphics and Imgaing, Innsbruck, Austria (2010)
Sarfraz, S.M., Hellwich, O.: An Efficient Front-end Facial Pose Estimation System for Face Recognition. International Journal of Pattern Recognition and Image Analysis 18(3), 434–441 (2008)
Do, N.M., Vetterli, M.: The Contourlet Transform: An Efficient Directional Multi resolution Image Representation. IEEE Transactions on Image Processing 14, 2091–2106 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zakir, U., Usman, A., Hussain, A. (2012). A Novel Road Traffic Sign Detection and Recognition Approach by Introducing CCM and LESH. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7665. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34487-9_76
Download citation
DOI: https://doi.org/10.1007/978-3-642-34487-9_76
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34486-2
Online ISBN: 978-3-642-34487-9
eBook Packages: Computer ScienceComputer Science (R0)