Detection and classification of speed limit traffic signs

Abstract

This conference paper was presented in the World Congress on Computer Applications and Information Systems, WCCAIS 2014; Hammamet; Tunisia; 17 January 2014 through 19 January 2014 [© 2014 IEEE] The conference paper's definite version is available at: http://dx.doi.org/10.1109/WCCAIS.2014.6916605This 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.Publishe

Automatic Speed-Limit Sign Detection and Recognition for Advanced Driver Assistance Systems

“…In this paper we presented Speed-Limit Sign Recognition system which is important part of the ADAS system, since it provides the alerts for the driver about speed limit to improve the traffic flow efficiency and safety of the driver. Mostly, the TSR consists of two stages, [3]. In detection stage, Region of Interest is detected and in classification stage, sign will be classified as particular class.…”

“…The drawbacks of these color based detection method is mainly due to changing in lighting conditions and blurriness in images. Rubel Biswas and Hasan Fleych [3] presented a system that uses shape based method i.e., Circular Hough Transform for detection, property curve [3] and SVM classifier for Classification. In this circular shaped traffic signs was used which requires more computation time.…”

Circular Traffic Sign Classification Using Hog Based Ring Partitioned Matching

“…Traffic sign recognition (TSR) system is one of the popular and challenging topics in the DAS. Basically, TSR consists of two steps [3][4][5][6][7][8][9][10][11][12][13][14][15][16]: traffic sign detection and classification. Traffic sign detection is used to detect the appearance of the traffic sign on an image.…”

“…In the classification process, the traffic sign is classified into the predefined one, such as the 50 km/h speed limit sign, the stop sign, etc. This paper deals with the classification of traffic signs, specifically the circular traffic signs as treated in [4], [10], [14], [17].…”

“…The SVM was employed to classify the digit of speed limit sign [4]. The SVM was trained by the curve feature which represented the pixel's intensity of digit number in each column.…”