To solve the problem that industrial robots cannot place products correctly due to mechanical positioning error in fast beat handling task, this article proposes a two-step strategy for two-point corrective positioning based on the improved Blob analysis. The first step identifies the positioning points based on machine vision and image processing techniques using the improved Blob analysis method. The second step quickly locates the position of a large number of products using the principle of planar affine transformation. The improved Blob analysis method is based on image grayscale inversion, histogram equalization, and image filtering techniques combined with threshold watershed segmentation algorithms to achieve reliable segmentation and circle center coordinate extraction for locating circular features in black pallet images that are not easily imaged under limited lighting conditions. Therefore, the two-point positioning strategy could achieve the planar affine transformation matrix before and after the pallet offset based on the reliable pallet circle center position results to complete the pallet offset correction function. Finally, the experiments at the handling station of the actual production line demonstrate that the accuracy and recall rate of the two-step strategy of two-point deflection correction positioning based on the improved Blob analysis are 99. 75% and 99. 75% , respectively, while the product handling time is reduced by 20. 52% . The reliability and efficiency of the robot unloading system are improved.