Multiple vehicle segmentation method based on optimum threshold values and random labeling method for multiple vehicles

The invention relates to a multiple vehicle segmentation method based on optimum threshold values and random labeling method. The method comprises the steps of image acquisition, image color space alternation, threshold value coarse segmentation of image, fine segmentation of images, background pickup and updating, and the like. In the coarse segmentation of image, an energy function is established according to the restriction relation relative to the threshold values, and the optimum double threshold values is computed with simulated annealing algorithm for image segmentation, therefore, thesegmentation efficiency is improved. In the background pickup and updating, with the selective background updating method in which similarity determines background updating speed, the calculation amount for segmentation is reduced and the real-time property is improved. According to the method, the vehicles can be segmented and detected correctly under the environment of hardest and softest illumination or horizontal and longitudinal shadows, and the method is suitable for road traffic management under outdoor environment, or other similar situations. A camera and a computer system are mainlyadopted for the implementation of the method, and the method can be applied in traffic monitoring and fields concerning traffic monitoring.