为了研制高性能的车辆牌照自动识别系统，在详细分析车辆牌照上英文和数字字符结构特点的基础上，选择字符图象中的闭合曲线作为其整体特征，将笔画端点，三叉点和四叉点作为其细节特征，同时将笔画中的拐角点作为其辅助结构特征，三者可分别用于字符的粗分类，细分类和相似字符区分，进而提基于图论和细节点特征的闭合曲线检测算法以及基于二值图象外边缘轮廓线的笔画拐角点检测算法，将上述结构特征用于车辆牌照上英文和数字字符识别，测得识别率达96％，用PⅢ550计算机完成结构特征抽取和字符识别所用时间约20ms／字符，表明这些结构特征适用于车辆牌照上英文和数字字符的快速识别。

In this paper the structural properties of alphabetic and digital characters on vehicle license plate are analyzed in detail and three types of feature are extracted for their recognition. These features include (a) global ones, i.e. closed curve in character, which can be used for character coarse classification; (b) minutiae, which are some key points in thinned image such as endings, bifurcations and crossings of strokes and can be used for character precise classification, (c) corners in strokes which can be used to discriminate similar characters. Algorithms for fast detection of closed curve based on theory of graph and minutiae and for corner finding based on external contour lines of binary image are also discussed. The recognition rate of alphabetic and digit character of the system based on these structural features is approximate to 96% and the time for feature extraction and character recognition is about 20ms/character. This shows that the proposed structural features have good discriminating power of similar characters and can be used for the fast classification and recognition of characters on vehicle license plate.