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Road Sign Detection and Recognition by using Local Energy Based Shape Histogram (LESH)
Usman Zakir, Iffat Zafar, Eran A. Edirisinghe
Pages - 567 - 583     |    Revised - 31-01-2011     |    Published - 08-02-2010
Volume - 4   Issue - 6    |    Publication Date - January / February  Table of Contents
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KEYWORDS
Contourlet Transform, LESH, HSV, Road Signs
ABSTRACT
The paper describes an efficient approach towards road sign detection and recognition system. The system is divided into three sections I) Segmentation of road traffic signs using HSV colour space under varying lighting conditions II) Shape Classification by using contourlet transform considering occlusion and rotation of the candidate sign III) and the Recognition of the road traffic sign is performed by using Local Energy based shape histogram. The algorithm described in this paper is robust enough to detect and recognize road sign under varying weather, occlusion, rotation and scaling conditions.
CITED BY (16)  
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12 Zakir, U., Usman, A., & Hussain, A. (2012, November). A novel road traffic sign detection and recognition approach by introducing CCM and LESH. In Neural Information Processing (pp. 629-636). Springer Berlin Heidelberg.
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Mr. Usman Zakir
- United Kingdom
u.zakir@lboro.ac.uk
Mr. Iffat Zafar
- United Kingdom
Dr. Eran A. Edirisinghe
- United Kingdom