文章基本信息

标题：3-D Offline Signature Verification with Convolutional Neural Network
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作者：Na Tyrer ; Fan Yang ; Gary C. Barber 等
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2020
卷号：10
期号：15
页码：221-228
DOI：10.5121/csit.2020.101518
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Signature verification is essential to prevent the forgery of documents in financial, commercial, and legal settings. There are many researchers have focused on this topic, however, utilizing the 3-D information presented by a signature using a 3D optical profilometer is a relatively new idea, and the convolutional neural network is a powerful tool for image recognition. The present research focused on using the 3 dimensions of offline signatures in combination with a convolutional neural network to verify signatures. It was found that the accuracy of the data for offline signature verification was over 90%, which shows promise for this method as a novel method in signature verification.
关键词：Signature Verification ;3D Optical Profilometer ;Convolutional Neural Network.