Signature Recognition using Siamese Neural Networks

Voruganti Ajay Krishna, AtthapuramAkshay Reddy, D. Nagajyothi
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Abstract

The traditional role of a signature is to permanently affix a person’s uniquely identifiable, self-identification to a document as physical evidence of that person’s personal witness and certification of the content of the entire document, or a selected portion of it. Yet with the technology advancement and tools available now a day it is easy to catch the culprits with artificial intelligence and neural networks. The neural network we used is Siamese neural network which is an artificial neural network which takes in similar input vectors and produces comparable output vectors. We are trying to make a user friendly interface using modern web technologies and the most data science language python and a simple Flask backend using python, the model is trained as per the signature images uploaded to a form on a local server then the images are taken and fed to the Siamese neural network to predict if they are forged or not and the results are going to be displayed in a user friendly format in the homepage.
使用连体神经网络的签名识别
签名的传统作用是将一个人的唯一可识别的自我身份永久地附加到文件上,作为该人个人见证的实物证据和整个文件或其中选定部分内容的证明。然而,随着技术的进步和工具的使用,利用人工智能和神经网络很容易抓住罪魁祸首。我们使用的神经网络是暹罗神经网络,这是一种人工神经网络,它接受相似的输入向量并产生相似的输出向量。我们正在尝试使用现代web技术和最具数据科学语言python以及使用python的简单Flask后端来制作一个用户友好的界面,该模型根据上传到本地服务器上的表单的签名图像进行训练,然后将图像拍摄并馈送到Siamese神经网络以预测它们是否伪造,结果将以用户友好的格式显示在主页上。
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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