Signature analysis system using a convolutional neural network

Alicja Winnicka, K. Kesik, Dawid Połap
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引用次数: 1

Abstract

Identity verification using biometric methods has been used for many years. A special case is a handwritten signature made on a digital device or piece of paper. For the digital analysis and verification of its authenticity, special methods are needed. Unfortunately, this is a rather complicated task that quite often requires complex processing techmques. In this paper, we propose a system of signatures verification consisting of two stages. In the first one, a signature pattern is created. Thanks to this, the first attempt to verify identity takes place. In the case of approval, the second stage is followed by the processing of a graphic sample contaimng a signature by the convolutional neural network. The proposed techmque has been described, tested and discussed due to its practical use.
签名分析系统采用了卷积神经网络
使用生物识别方法进行身份验证已使用多年。一种特殊情况是在数字设备或纸上手写签名。为了对其真实性进行数字分析和验证,需要采用特殊的方法。不幸的是,这是一项相当复杂的任务,通常需要复杂的处理技术。本文提出了一个包含两个阶段的签名验证系统。在第一个示例中,创建了一个签名模式。由于这一点,验证身份的第一次尝试发生了。在批准的情况下,第二阶段是卷积神经网络处理包含签名的图形样本。由于其实际应用,所提出的技术已被描述、测试和讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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