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Recognition Stage for a Speed Supervisor Based on Road Sign Detection
Intelligent Systems Lab, Universidad Carlos III de Madrid, Avda de la Universidad 30, 28911 Leganes, Spain
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Received: 23 July 2012; in revised form: 30 August 2012 / Accepted: 31 August 2012 / Published: 5 September 2012
Abstract: Traffic accidents are still one of the main health problems in the World. A number of measures have been applied in order to reduce the number of injuries and fatalities in roads, i.e., implementation of Advanced Driver Assistance Systems (ADAS) based on image processing. In this paper, a real time speed supervisor based on road sign recognition that can work both in urban and non-urban environments is presented. The system is able to recognize 135 road signs, belonging to the danger, yield, prohibition obligation and indication types, and sends warning messages to the driver upon the combination of two pieces of information: the current speed of the car and the road sign symbol. The core of this paper is the comparison between the two main methods which have been traditionally used for detection and recognition of road signs: template matching (TM) and neural networks (NN). The advantages and disadvantages of the two approaches will be shown and commented. Additionally we will show how the use of well-known algorithms to avoid illumination issues reduces the amount of images needed to train a neural network.
Keywords: ADAS; detection; recognition; road signs; pattern matching; neural network
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Cite This Article
MDPI and ACS Style
Carrasco, J.-P.; de la Escalera, A.E.; Armingol, J.M. Recognition Stage for a Speed Supervisor Based on Road Sign Detection. Sensors 2012, 12, 12153-12168.
Carrasco J-P, de la Escalera AE, Armingol JM. Recognition Stage for a Speed Supervisor Based on Road Sign Detection. Sensors. 2012; 12(9):12153-12168.
Carrasco, Juan-Pablo; de la Escalera, Arturo de la Escalera; Armingol, José María. 2012. "Recognition Stage for a Speed Supervisor Based on Road Sign Detection." Sensors 12, no. 9: 12153-12168.