Lane Marking Detection in Various Lighting Conditions using Robust Feature Extraction

Robustly extracting the features of lane markings under different lighting and weather conditions such as shadows, glows, sunset and night is the a key technology of the lane departure warning system (LDWS). In this paper, we propose a robust lane marking feature extraction method. By useing the characteristics of the lane marking to detect candidate areas. The final lane marking features are extracted by first finding the center points of the lane marking in the candidate area then these center point pixels are labeled according to the intensity similarity along the direction of the vanishing point. The performance of the proposed method is evaluated by experiment at results using real world lane data.