Design and research on the motion target detection and tracking algorithm

As the common technique used in the monitoring system, Motion Detection Technology generally conducts tracking by finding motion trace of targets through the analysis of video frame sequence, however, the high efficiency and validity of target pattern matching can not be guaranteed. By means of the characteristics of Gaussian distribution and scaling density functions, this paper has studied and designed a kind of algorithm for detecting and tracking moving target, which can realize foreground detection on the moving target, achieve background update of Gaussian distribution model by updating weights, mean values and variance, and then extract foreground object by the noise reduction preprocessing for collecting image and the histogram equalization method, to determine the minimum Euclidean distance based on the space distance target tracking algorithm and thereby achieve the detection and tracking for the moving targets. Based on the experimental data, it is shown that the algorithm designed by the system can achieve the detection and tracking for the moving targets under the condition that the hardware is at rest.