Aiming at the problems of low accuracy and robustness of rail detection and recognition methods and poor fitting of curved rail, a rail detection and recognition algorithm based on straight-curve hybrid model is proposed. In the beginning, the image is preprocessed and Canny edge detection is completed by adjusting the lag threshold. The Progressive Probabilistic Hough Transform is used to detect the direct straight track, divide the near and far field of view and determine the vanishing point. The straight track in the near field is fitted by a linear model, and the feature points of the rail are obtained by the circular linear approximation of the far field according to the detection results, and verified according to the gray characteristics of the rail. The least square method is used to complete the curve fitting. The switch of straight-curve model is completed according to the established rules. Experimental results show that the detection accuracy of the proposed algorithm is 90. 1%, which is suitable for different environments and has good robustness.