Automatic Verification of Handwritten Signature

个人自动识别是信息社会发展的一大研究课题。我们指出，作家的签名书法具有个人特征。在对个人的认识中，重要的目标如下。1)在书法中，找出包含个人特征的字辨别一个作家的书法运用笔迹的特点，是否有效。在这项研究中，我们从离线的字母签名中提取了一些个人特征。首先，我们分别使用模糊度函数来保证特征的有用性。接下来，结合这些有用的特征，我们降低了识别的模糊程度。同时，我们引入了文字的顺序信息这一新的特征。我们喜欢总结如下。1)结合使个体笔迹的辨识模糊程度最小化的特征，实现了判别因子91.7%。2)为了通过辨识系统提升整体效率，我们选取了每个签名中常见的辨识特征。在本例中，判别因子为88.5%，判别时间约为1秒。同时，对于这种签名的离线判别，引入写序信息是一种新的尝试，阐明了该尝试的实用性。这一点值得一提。

Automatic recognition of the individual is a big research theme on advances of the information society. We pointed out that there are personal characteristics in a writer's calligraphy of the signature.In the recognition of individual, important aims are as follows.1) In a calligraphy of handwriting, founding out the charactes which the individual characteristics are included.2 Discrimination of a writer's calligraphy of handwriting using the characteristics, effectively.In this research, we extracted some kind of personal characteristics from an alphabet signature in offline. 1st of all, we assured usefulness of the characteristics using a vagueness degree function, individually. Next, by combination of these useful characteristics, we reduce the vagueness degree of discrimination. By the way, we introduced the order information of writing as a new charactristics.We like to summarize as follws.1) In combination with characteristics which minimize the vagueness degree of discrimination for an individual writer's calligraphy, we realized discriminant factor 91.7%2) In order to level up total efficiency through the discrimination system, we selected the characteristics of discrimination in common each signature.In this case, the discriminant factor is 88.5% and the discriminant time isabout 1 sec. And also, to this offline discrimination of signature, introduction of the write order information is new trial, usefulness of the trial was clarified. This is worthy of special mention.