通过人脸识别和检测进行智能投票

Shaista Khan, Manisha Dwara
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引用次数: 0

摘要

面部识别工具是一种可以从数字图像或视频来源中识别或验证人的技术。面部识别系统的工作方式有很多,但通常它们是通过将数据库中给定图像中的选定面部特征与人脸进行匹配来工作的。它也被称为基于人工智能的生物识别应用程序,可以通过分析基于个人面部纹理和形状的模式来唯一地识别一个人。在此方法中,我们使用三个身份验证步骤来对将要使用的选举人进行验证。第一步是验证身份证,第二步是验证选民卡号码,第三步是验证,其中包括不同的面部识别算法。我们将在本文中对这些算法进行比较分析,即:FisherFace, SURF和Eigenface。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent voting via face recognition and detection
A tool for facial recognition is a technology that can recognise or verify a person from a digital image or from a source of video. There are many ways facial recognition systems work, but usually they work by matching selected facial features within a database from a given image with faces. It is also known as a Biometric Artificial Intelligence-based application that can uniquely identify a person by analysing patterns based on the individual’s facial textures and shape. In this method, we use three authentication steps for the electors will be used. The first step is the verification of the UID, the second step is the number of the voter card and the third step is the verification, which includes different algorithms for facial recognition. We will offer a comparative analysis between these algorithms in this paper, namely: FisherFace, SURF & Eigenface.
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