Application of convolutional neural networks and image processing algorithms based on traffic video in vehicle taillight detection

Ning Cao, Wei Huo, Taihe Lin, Gangshan Wu

Abstract: In the process of assisted driving, accurately understanding the linguistic information transmitted by surrounding vehicles is the prerequisite for making correct driving decisions. In this paper, the neural network was partly used for vehicle detection. The recognition of the front vehicle taillights is based on the taillight recognition mechanism and image processing technology. The taillights are then positioned by using their colour and shape characteristics. The red-green-blue (RGB) and cyan-magenta-yellow (CMY) colour spaces were used to establish a taillight recognition mechanism to detect the taillight status of the front car, so as to understand the driving intention of the front car. The experimental results show that the method can accurately identify the state of the front taillights during the day.