Target detection method for vehicles and pedestrians in intelligent traffic monitoring

The invention discloses a target detection method for vehicles and pedestrians in intelligent traffic monitoring. The method comprises the following steps of: performing background model initialization on a video frame sequence, independently establishing hybrid Gaussian background component models for a saturation component and a brightness component, and calculating component mean values; differentiating a current frame in the video frame sequence from a background frame, performing binarization processing on a foreground frame, removing shadows and noises and performing morphological filtering; updating weight values, mean values and variances of the components of an obtained hybrid Gaussian background model by using an updating factor; and comparing values of moving target pixels to be matched with each distributed Jeffrey value in the updated hybrid Gaussian background model, and judging whether the moving target pixels are foreground points or not by utilizing the Jeffrey values. By utilizing the method, related parameters of the saturation component and the brightness component are required to be updated, so the overhead of a system is decreased under the condition of not influencing the precision, and the influence of noises and environmental illumination can be avoided; and the method can adapt to the slight disturbance of scenes, and has the characteristic of high robustness.