Abstract
In recent years, more and more traffic accidents have been caused by the illegal use of high beams. Therefore, the distinguishing of the vehicle headlight is vital for night driving and traffic supervision. And then, a method for distinguishing vehicle headlight based on data access of a thermal camera was proposed in this paper. There are two steps in this method: The first step is thermal image dynamic adjustment. In thermal image dynamic adjustment, the details of thermal images were enhanced by adjusting the temperature display dynamically and fusing features of multi-sequence images. The second step is vehicle headlight dynamic distinguishing, and features of vehicle headlight were extracted by YOLOv3. Then, the high beam and low beam were further distinguished by the filter based on the position and proportion relationship between the halo and the beam size of vehicle headlights. In addition, the accessed thermal image dataset during the night was used for training purposes. The results showed that the precision of this method was 94.2% and the recall was 78.7% at a real-time speed of 9 FPS. Compared with YOLOv3 on the RGB image, the precision was further improved by 11.1%, and the recall was further improved by 5.1%. Dynamic adjustment and distinguishing method was also applied in SSD network which has good performance in small object detection. Compared with SSD network on the RGB image, the precision was improved by 8.2% and the recall was improved by 4.6% when SSD network was improved by this method.
Highlights
INTRODUCTIONTraffic accidents have become a common problem for vehicle drivers. The risk of traffic accidents on an unlit road is about 1.5–2 times higher than that during the day [1]
In recent years, traffic accidents have become a common problem for vehicle drivers
For training and testing purposes, the data were accessed from thermal cameras in the urban nighttime road
Summary
Traffic accidents have become a common problem for vehicle drivers. The risk of traffic accidents on an unlit road is about 1.5–2 times higher than that during the day [1]. Thermal Image Enhancement In the case of low illumination at night, the vehicle characteristics can be disturbed by the halo of the headlights, so that the camera cannot capture the contour of a vehicle. The contour features of vehicle headlight can be extracted by the Sobel operator, as shown in Equation (3) Because it can obtain the edge of target which has a great gradient with background, the Sobel operator on a preprocessed image in order to retrieve an edge image is used to find and extract a rectangular area in the original image which represents the license plate [21, 22]. The halo areas of vehicle headlight SLight in the RGB image can be obtained after threshold processing [22]. The discrimination conditions of the low and high beams satisfy the following relationship in Equation (9)
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