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An evaluation on offline signature verification using artificial neural network approach

机译:人工神经网络方法对脱机签名验证的评估

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摘要

The signature verification is the oldest security technique to verify the identification of persons. Recently, the signature recognition schemes are growing in the world of security technology. It offers two different types of schemes those are offline and online method. The offline technique means to verify a signature written on paper which is scanned to convert it into a digital image, whereas the online system required an online device such as Tablet PC, touch screen monitor by a pressure sensitive pen to verify the signature. This paper discusses a review of offline signature verification schemes which considered as a highly secured technique to recognize the genuine person's identity. It addresses the offline signature verification technique using Artificial Neural Network (ANN) approach. It also explains the fundamental characteristics of offline signature verification processes and highlights the comparison among various offline signature verification approaches and various signature recognition issues.
机译:签名验证是验证人员身份的最古老的安全技术。最近,签名识别方案在安全技术领域正在不断发展。它提供两种不同类型的方案,即离线方法和在线方法。离线技术意味着验证纸上签名,然后将其扫描以将其转换为数字图像,而在线系统则需要使用诸如Tablet PC,压敏笔的触摸屏监视器之类的在线设备来验证签名。本文讨论了脱机签名验证方案的回顾,该方案被认为是识别真实身份的一种高度安全的技术。它解决了使用人工神经网络(ANN)方法的脱机签名验证技术。它还说明了脱机签名验证过程的基本特征,并重点介绍了各种脱机签名验证方法与各种签名识别问题之间的比较。

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