In view of the problems that the traditional Gaussian mixture model is easy to be disturbed by environmental noise or illumination change,and the detection results have holes and missing edges,a moving target detection algorithm based on adaptive Gaussian mixture model and inter-frame difference was proposed.At the beginning of the establishment of Gaussian mixture model,a large learning rate was used to quickly eliminate the background interference information.When the model tended to be stable,the learning rate was continuously adjusted according to the target motion state to realize adaptive correction of the background model.At the same time,a light change factor was introduced to adjust the model update rate and effectively overcome the influence of light change.In order to improve the continuity of the target edge,the four-frame difference method based on image similarity and edge detection algorithm were used to extract the contour information of the target and fill the target edge.The target cavity and residual noise were eliminated by morphological processing to obtain a complete moving target.The results show that the target detection accuracy of this method reaches 95.2%,and it has good adaptability and robustness to complex scenes while ensuring real-time performance.