License Plate Detection Using Bayesian Method Based on Edge Features

摘要

Due to the complexity and variability of lighting conditions, weather conditions, and the location relationship between vehicles and cameras, the license plate detection in complex scenes has an important application value. In this paper, based on the full analysis of the edge features of license plate area in complex scenes, a new fusion image preprocessing method using edge features is proposed, and the rectangular box similar to license plate area is taken as the candidate box. The experimental results show that the accuracy of the location of license plate area under different conditions reaches 98.31%. Based on the result of coarse location, we propose a Bayesian classifier to realize accurate location of vehicle license plate. This classifier makes full use of the high efficiency of Bayesian method to process low dimensional data and the credibility of probability calculation distribution. The model in different conditions on achieved 91.59% precision. The results of comparison with other classifiers show that the method in this paper is very robust to license plate detection in complex scenarios.