【摘要】 针对目前签名采集设备只能获得书写压力信息或不能同时获得书写力信息与字形信息的不足,采用自行研制的 F_Tablet 手写平台同时采集签名书写过程中的二维字形信息和三维书写力信息,并提出一种综合利用字形信息与书写力信息进行在线签名鉴别的方法.该方法先对签名进行预处理和笔画分割,并基于签名笔画数目建立多个签名模板,然后采用概率统计和迭代实验确定书写力内部以及书写力与字形之间的权重比和个性化的判别阈值,实现对签名的分类.基于利用 F_Tablet 手写平台构建的签名样本库的签名鉴别实验结果证明了本文提出的基于字形信息和书写力信息的在线签名鉴别方法的有效性.更多还原

【Abstract】 To solve the problem that the present signature collecting devices are not able to get the writing forces and signature shape simultaneously or only get the writing pressure,a self-devised F_Tablet writing tablet is used to collect the two-dimension signature shape and three-dimension forces during writing.And a novel technique using stroke segmentation,multi-template and iterative experiment puts forward to verify the signatures with signature shape and writing forces.The validity of this technique is proved by the experimental results based on the signature database constructed with F_Tablet.更多还原