A sub-pixel stripe center extraction method leveraging the Gaussian-weighted grayscale center of gravity and density clustering is proposed. This approach addresses the limitations of traditional strip extraction algorithms, particularly their susceptibility to interference and the need for enhanced efficiency. The proposed method successfully extracts the center line of the light bar for images with noise points. The effective light-stripe information in the image is first extracted using the single channel extraction, gamma correction, and Otsu method. The light-stripe centerline is then initially fitted using the Gaussian-weighted grayscale center of gravity method. Finally, the light-stripe centerline is further accurately fitted using the density clustering algorithm. The method achieves a root mean square error of approximately 0.72 pixels and exhibits a maximum fluctuation of 13.6% under conditions of fewer than 1 000 random noise points. In terms of performance, the proposed method demonstrates a 4.8-fold increase in efficiency compared to the conventional Steger algorithm, with a minimal loss of 9.2% in accuracy.