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http://dx.doi.org/10.5302/J.ICROS.2015.15.0133

Traffic Light Detection Using Morphometric Characteristics and Location Information in Consecutive Images  

Jo, Pyeong-Geun (Department of Industrial Engineering, Chonnam National University)
Lee, Joon-Woong (Department of Industrial Engineering, Chonnam National University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.21, no.12, 2015 , pp. 1122-1129 More about this Journal
Abstract
This paper suggests a method of detecting traffic lights for vehicles by combining the HSV(hue saturation value) color model, morphometric characteristics, and location information appearing on consecutive images in daytime. In order to detect the traffic light, the color corresponding to the signal lights should be explored. It is difficult to detect traffic lights among colors of lights from buildings, taillight of cars, leaves, placards, etc. The proposed algorithm searches for the traffic lights from many candidates using morphometric characteristics and location information in consecutive images. The recognition process is divided into three steps. The first step is to detect candidates after converting RGB channel into HSV color model. The second step is to extract the boundaries between the housing of traffic lights and background by exploiting the assumption that the housing has lower brightness than the surrounding background. The last step is to recognize the signal light after eliminating the false candidates using morphometric characteristics and location information appearing on consecutive images. This paper demonstrates successful detection results of traffic lights from various images captured on the city roads.
Keywords
traffic light detection; HSV color model; morphometric characteristics; location information;
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Times Cited By KSCI : 1  (Citation Analysis)
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