Robust Detection of Lighting LEDs by Analyzing the Geometric Structure of the Tunnel Interior Environment in Vehicle-Mounted Video Sequences

Tunnel LED lighting system is an important infrastructure to ensure the safety and comfort of driving in highway tunnels. In this paper, an automatic robust detection of lighting LED lamps in highway tunnels based on vehicle-mounted video processing is proposed. By analyzing the geometric structure of the interior road environment in tunnels, this method includes the following three aspects. Firstly, the front-vehicle vanishing point is detected by using the M-estimator sample and consensus (MSAC) algorithm, just with the set of significant parallel lines extracted using the LSD (Line Segment Detector) operator. Secondly, after the dark region on the top of the tunnel is accurately segmented, an image segmentation algorithm based on adaptive threshold is adopted, realizing the LED lamp candidate region detection. Thirdly, this paper proposes post-processing methods to ensure the accurate detection of LED lamps in complex scenes with highlight-interference in the tunnel. The experimental results show that this method can robustly detect the LED lamps in the tunnel under complex conditions with high accuracy, which can meet the needs of efficient acceptance inspection and daily maintenance of tunnel LED lighting system.