Abstract:

Aiming at solving several problems in vehicle detection,  a GMM (Gaussian Mixture Model) detection algorithm based on distribution of matching rate was proposed. The algorithm got the initial value of GMM with c mean clustering method, which formed the original background model. It fully took the timeliness and spatiality into consideration by proposing the concept of distribution of matching. And it changed the learning rule of background of current frame to eliminate interference and adapt to the change of background according to the distribution of matching rate corresponding to the former several frames. The experimental results indicate that the algorithm improves the detection rate by at least over 16%. The updated background is also more stable and accurate. It overcomes the problems of fracture of vehicle detection and saltation of illumination and improves the accuracy of detection of vehicle region.

Key words: vehicle detection, gaussian mixture model (GMM), background subtraction, distribution of matching rate