提出一种在复杂环境下进行实时车牌定位的新方法。先根据车牌图像的边缘特征,利用多级边缘点距离生成连通区域,搜索全图得到连通域的最小外接矩形。然后利用车牌本身的拓扑特征和颜色特征进行判别,提取候选区域。与同类方法相比,该方法限制条件少、速度快、准确率高。对526幅各种环境下实际采样图像进行实验,定位成功率为98.3%,平均定位时间少于40m s。

This paper presents a novel algorithm for license plate detection in complex environments.The algorithm generates connective components by hierarchical distances between edge points based on vehicle edge map and then gets the relevant minimum enclosing rectangular by searching the whole map.Afterwards,it picks up candidate regions of plates according totopological characteristics and color features.In this paper,least constraints are imposed on the working environment.In the experiment for locating license plates,526 images taken from various scenes and under different conditions were processed with an accuracy of 98.3%.At the same time,the average locating time is less than 40ms.