一种新的字符特征向量相似度函数  

A new character feature vector similarity function

作　　者：李宇成[1] 田震[1] 游加[1] 

机构地区：[1]北方工业大学自动化系,北京100144

出　　处：《计算机工程与科学》2013年第5期93-99,共7页Computer Engineering & Science

摘　　要：为分析车牌字符特征向量和比较字符特征提取方法,在街区距离的基础上构造了一种线性相似度函数的定义sim(M,N),讨论了该相似度函数的相关性质,给出了完全不相似概念的数学解释。与几种常见的相似度函数相比,sim(M,N)能够线性、平权地直接反映向量中各分量的差异,且计算极为简单。分析、比较了欧氏距离与sim(M,N)在分析字符特征向量方面的差异,并通过实验证实了欧氏距离的不足。通过车牌中相似字符的平均可分裕度实验,表明在比较字符特征向量方面,sim(M,N)能够获得整体好于几种常见相似度函数的使用效果。To analyze the feature vectors of vehicle plate characters and its extraction method, this paper proposed a linear similarity function definition sire （M,N） based on city-block distance, discussed the properties of this similarity function, and gave the mathematic explanation of completely dissimilarity. Compared with some common similarity functions, sim （M, N） can describe feature vector differences linearly and the computation is very easy. Meanwhile, the paper discussed the differences between Euclidean distance and sire （M,N） in analyzing feature vector differences, and proved the shortage of Euclidean distance through experiments. In the average character margin experiment of similar vehicle plate characters, sire （M,N） is demonstrated to be better than other similarity functions.

关 键 词：线性相似度函数 字符平均可分裕度 字符特征向量 

分 类 号：TP391.43[自动化与计算机技术—计算机应用技术]