In the optical lens defect detection, in order to improve the accuracy and speed of the optical lens image threshold segmentation, a new particle swarm optimization (PSO)+Otsu threshold segmentation algorithm is proposed. The algorithm improves the PSO weight factor update strategy, increases the time when the weight factor is at a larger value at the beginning of the iteration, enhances the global search ability, calculates the optimal position of the particle, and assigns the optimal position to the Otsu algorithm. Finally realize the threshold segmentation of the optical lens image. The improved weight factor update strategy can overcome the shortcomings of the typical linearly decreasing weight factor update strategy that the global search ability at the initial stage of the iteration is insufficient, which leads to the local extreme value in the later stage. Experimental results show that this algorithm improves the speed of threshold segmentation while improving the accuracy of image threshold segmentation.