This paper designs a lane line detection algorithm for multi-road scenes based on Raspberry Pi embedded platform in the image preprocessing stage. In the image preprocessing stage, an adaptive binarization extraction algorithm for lane lines is designed. By comparing the pixels to be measured with the vertices of the diamond space where they are located, the binarized lane line information is completely extracted. at the same time, combined with the method of maximum classes error (OTSU), the interference information is effectively filtered out by means of image fusion. In the lane line fitting stage, the slope constraint and distance limitation of the Progressive Probabilistic Hough Transform are improved, and the edge points of the lane line are accurately calculated after further filtering out interference information. Finally, the least squares method is used to fit the lane line. The test results show that the algorithm has a stronger anti-interference ability, and the detection accuracy of multiple road scenes can reach 90.24%. And the running speed on the Raspberry Pi platform is 25fps, which meets the real-time requirements.