A Real-Time System for Detecting Illegal Changes-of-Lane Based on Tracking of Feature Points

This paper proposes a real time system for detecting vehicles that change lanes illegally based on tracking the feature points. The proposed system consists of three stages, which take part of the roles such as feature extraction of corners, registration and tracking the feature points attached to vehicles, and detecting a vehicle that violates legal lane changes. In the stage of feature extraction, we used a fast algorithm that can provide stable corners. The salient points are again selected among the corner points for registration and tracking. NCC (normalized cross correlation) is used to keep tracing the registered feature points. Finally, illegal change-of-lane is detected by the information about the traced corners. As a result of experiment, the proposed system showed excellent performance as amount of 99.09% of correct detection ratio and 0.9% of error. The fast processing could deal with 34.48 frames per second, which is sufficient for real-time processing.