NDLI: Detection and classification of speed limit traffic signs

Content Provider	IEEE Xplore Digital Library
Author	Biswas, R. Fleyeh, H. Mostakim, M.
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Sci. & Eng., BRAC Univ., Dhaka, Bangladesh (Biswas, R.; Mostakim, M.) \|\| Comput. Eng. Dept., Dalarna Univ., Falun, Sweden (Fleyeh, H.)
Abstract	This paper presents a novel traffic sign recognition system which can aid in the development of Intelligent Speed Adaptation. This system is based on extracting the speed limit sign from the traffic scene by Circular Hough Transform (CHT) with the aid of colour and non-colour information of the traffic sign. The digits of the speed limit sign are then extracted and classified using SVM classifier which is trained for this purpose. In general, the system detects the prohibitory traffic sign in the first place, specifies whether the detected sign is a speed limit sign, and then determines the allowed speed in case the detected sign is a speed limit sign. The SVM classifier was trained with 270 images which were collected in different light conditions. To check the robustness of this system, it was tested against 210 images which contain 213 speed limit traffic sign and 288 Non-Speed limit signs. It was found that the accuracy of recognition was 98% which indicates clearly the high robustness targeted by this system.
Starting Page	1
Ending Page	6
File Size	1676247
Page Count	6
File Format	PDF
ISBN	9781479933501
e-ISBN	9781479933518
DOI	10.1109/WCCAIS.2014.6916605
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-17
Publisher Place	Tunisia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Image segmentation Image color analysis Roads Digit Segmentation Transforms Classification Traffic sign Real-time systems SVM Circular Hough Transform Vehicles
Content Type	Text
Resource Type	Article

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