A fundamental way to improve the automation level of pipeline welding in industries is to quickly and accurately identify the weld. To solve this problem, we designed a laser vision-guided seam tracking system for pipeline bus weld. The seam image containing laser stripes was obtained using a CCD industrial camera, and the position of the laser stripes was determined after digitizing the image, threshold segmentation, and region of interest area extraction. Then, we reduced the laser stripes in the images using the improved geometric center algorithm. Furthermore, we obtained the two-dimensional coordinates of the solder points using the curve fitting and feature point recognition algorithm. Finally, we reconstructed the three-dimensional weld feature points using the principle of camera imaging and transformed the coordinates of the weld points from the image coordinate system to the robot base coordinate system to guide the robot to autoweld. The experimental results show that the recognition errors of the solder joints are all within 0.5 mm. Additionally, the recognition efficiency and accuracy of the seam feature point extraction are high, which meet the production requirements of robot automatic welding.