An automatic tagging robot needs to be provided the 3D coordinates of a bar’s bottom center to weld a tag on the bundle. A method based on binocular vision was proposed to select and localize bars’ bottom centers. Virtual image camera model was adopted in the binocular vision system. The extrinsic parameters of two cameras were calibrated from a planar calibration pattern which was put parallel to the common end plane of bars. The virtual images of two cameras were created according to the calibrated results. A method using SVM and connected region was adopt to extract the center point features of bars in both virtual images from two cameras. A group of candidate features pairs were selected using epipolar constraint to the features and coplanar constraint to the recovered physical points. The 3D coordinates of corresponding physical points were recommended to the robot to try to weld the tag. Simulation results showed all recommended points to the robot were from correct matched pairs. It demonstrated effectiveness of the features matching method presented. In real experiment, the maximum depth displacement error of the recommended points was 0.20 mm, the average error was 0.09 mm. It demonstrated the effectiveness of bar bottom center extraction method presented.