The Vision-based Vehicle Detection and Incident Detection System in Hsueh-Shan Tunnel

Abstract

The automatic lane marking detection, vehicle detection and incident detection systems are proposed in this paper. The block-based background extraction that combines statistical algorithm and the moving block information is used to obtain the color background image more exactly. The lane detection algorithm is applied to obtain the lane information from the color background image without the limitation of the camera setting. The presented vehicle detection algorithm is a block-based approach which is widely used in highway systems, urban roadways or tunnels. Different applications adopt the different detection zones where the vehicles will be tracked and identified in. The presented incident detection algorithm focuses on the car stopped, vehicle lane changing, and congestion condition, and the experimental results in Hsueh-Shan tunnel are addressed, which also demonstrate the stability and the effectiveness of the proposed methods.