Infrared target detection based on Gaussian model and Hungarian algorithm

Based on Gaussian distribution, a method for modelling targets is proposed. The trajectories of infrared targets are predicted by Kalman filtering. The Munkres version of the Hungarian algorithm is utilized to find the optimum assignment between the trajectories and the positions of real targets. Finally, based on the open dataset, we prove that the proposed algorithm is able to find and track infrared dim targets more effectively, while satisfying the requirements of real-time detection.