|Appears in Collections:||Computing Science and Mathematics Book Chapters and Sections|
|Title:||A novel road traffic sign detection and recognition approach by introducing CCM and LESH|
|Citation:||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 (eds.) Neural Information Processing: 19th International Conference, ICONIP 2012, Doha, Qatar, November 12-15, 2012, Proceedings, Part III. Lecture Notes in Computer Science, 7665. Berlin Heidelberg: Springer, pp. 629-636. http://link.springer.com/chapter/10.1007/978-3-642-34487-9_76#; https://doi.org/10.1007/978-3-642-34487-9_76|
|Series/Report no.:||Lecture Notes in Computer Science, 7665|
|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.|
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