Self-adaptive threshold value moving object detection method based on codebook background model

The invention discloses a self-adaptive threshold value moving object detection method based on a codebook background model, which belongs to the technical field of intelligent video monitoring. The method comprises the following steps of (1) classifying an inputted video image sequence into a training set and a detection result set, and creating an initial codebook background model for the inputted training set through a self-adaptive threshold value method; (2) purifying and optimizing the created initial codebook background model through a time filtering way; (3) applying the purified codebook background model to the foreground detection, and subtracting the codebook background model adopting the front n frames of image which is used as a training sample as the training set by the subsequently inputted video image sequence; and (4) binarizing the obtained differential image, and utilizing the binary image as a final detection result image. By adopting the method, the threshold value can be self-adaptively adjusted, so that compared with the traditional detection method, the method has the advantages that a better detection result can be obtained, and the accuracy is high.