|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 CS (ed.). 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.|
|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.|
|Rights:||The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
|A novel road traffic sign detection and recognition approach by introducing CCM and LESH.pdf||300.07 kB||Adobe PDF||Under Embargo until 31/12/2999 Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact email@example.com providing details and we will remove the Work from public display in STORRE and investigate your claim.