Recognition Stage for a Speed Supervisor Based on Road Sign Detection

Sensors

Juan-Pablo Carrasco¹  Arturo de la Escalera² 

[1] Intelligent Systems Lab, Universidad Carlos III de Madrid, Avda de la Universidad 30, 28911 Leganes, Spain;

关键词: ADAS;    detection;    recognition;    road signs;    pattern matching;    neural network;   

DOI  :  10.3390/s120912153

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.