基于多特征和证据理论离线签名识别  

Off-line signature recognition based on multi-features and evidence theory

作　　者：张磊[1] 李弼程[1] 刘安斐[1] 

机构地区：[1]信息工程大学信息工程学院信息科学系,郑州450002

出　　处：《计算机工程与应用》2007年第8期234-237,共4页Computer Engineering and Applications

摘　　要：提出了一种基于多特征和证据理论的离线签名识别方法。首先通过比较各个特征在离线签名识别中的性能,选取比较有效的平均伪动态特征和中等分辨率网格特征作为识别特征,然后构造了两个K近邻(KNN,K Nearest Neighbor)分类器,对签名图像进行初步识别。在初步识别基础上,利用一种改进的证据理论合成公式,将两个KNN分类器的输出结果进行融合得到最终识别结果。实验结果表明新的识别方法是有效性。A off-line signature recognition method based on multi-features and evidence theory is introduced in this paper.Two effective features,pseudo dynamic feature and ＇grid feature,are selected by comparing the performance of features in off-line signature recognition.Then initial signature recognition result is done by two KNN classifiers.Next,the output from classifiers is used as evidence to get the final fusing result,which using a improved combined method based on evidence theory.Experiments show that this new recognition method is effective.

关 键 词：离线签名识别 动态特征 网格特征 K—NN分类器 证据理论 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]