基于模糊模型最优化规则的脱机签名鉴定研究  

Off-line Signature Verification Based on Optimal Rules of Fuzzy Modeling

作　　者：田伟[1] 乔谊正[1] 马志强[1] 

机构地区：[1]山东大学控制科学与工程学院,济南250061

出　　处：《模式识别与人工智能》2008年第1期122-127,共6页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金(No.60775023);山东省自然科学基金(No.Y2002G02;Z2005G03)资助项目

摘　　要：提出一种基于多模糊规则的脱机签名模糊鉴定系统.该系统提取签名的静态特征和伪动态特征以弥补书写过程中丢失的动态信息,并采用模糊集合表征所提取特征的不确定性,同时利用隶属度函数构建新的权重系数,反映不同模糊规则对鉴定结果的重要程度.另外,为减少整个模糊鉴定系统的复杂性,提出采用K-交叉验证方法对模糊规则数目的选择进行最优化.实验采用中、英文两种签名数据库分别得到9.52%和12.67%的平均错误率,验证了该系统的有效性.A new off-line signature verification system based on fuzzy modeling of multiple rules is proposed. In this system, both static and pseudodynamic features are extracted to make up for the loss of dynamic information and their variation is described by fuzzy sets. Then the new weight coefficients by the membership functions are devised to reflect the contribution of different fuzzy rules to verification results. In addition, the optimal selection of multiple rules by the reliable estimate of K -fold cross-validation is presented to reduce the computational complexity of the entire fuzzy system. Databases of Chinese and English signatures are applied to the experiments and the average error rates of 9. 52% and 12. 67% are obtained. Thus the effectiveness of the proposed system is validated.

关 键 词：脱机签名鉴定 模糊模型 最优化规则 K-交叉验证 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]