Research on the Detection Algorithm of Automobile Low Beam Feature Points Based on Point Symmetry Degree

Accurate detection of the feature points of automobile low beam is a crucial step in the alignment and adjustment of automobile low beam headlights. Its detection accuracy plays a decisive role in the accuracy and reliability of the comprehensive detection results of automotive headlamps. Moreover, it is an important technical support for ensuring the safety and compliance of vehicle lighting systems. However, the existing detection algorithms for low beam feature points cannot generally and effectively detect and distinguish the feature points of low beam with different low beam light patterns. Therefore, this paper proposes a new detection algorithm for the feature points of automotive low beam light patterns based on point symmetry degree. The core of this algorithm lies in making full use of the significant difference in point symmetry degree between corner points and non-corner points, and realizing the precise detection of low beam feature points based on this feature. The experimental results show that this algorithm can accurately identify and distinguish the elbow points and other feature points in the currently common “two-segment” and “five-segment” low beam light patterns. It has high detection accuracy, demonstrates strong universality and robustness, can effectively resist various interference factors, and has broad application prospects in the fields of automobile headlight optical detection and alignment adjustment.