In order to solve the effect of the image segmentation when the pedestrian image is collected by infrared camera, an image threshold segmentation algorithm based on adaptive particle swarm optimization of twodimensional OSTU is utilized. The gray scale of the current frame image and the neighborhood gray level of the current frame image pixel form a binary image. A 2D maximum betweencluster variance model is built up through calculating the average and variance between them, and combining with adaptive particle swarm optimization algorithm the best threshold image value is estimated. The algorithm can accurately estimate the threshold and reduce the calculation time. The simulation results demonstrate that the best image value is proper, the calculation time is shortened 50% when combine with adaptive particle swarm optimization algorithm. The proposed algorithm can get the optimal threshold quickly and accurately, and improve the segmentation effect of image preprocessing.