eKYC应用中的抗欺骗人脸识别技术

2021 3rd International Conference on Signal Processing and Communication (ICPSC) Pub Date : 2021-05-13 DOI:10.1109/ICSPC51351.2021.9451703

Sudarshan Paul, P. Bruntha, A. Raj, Saurabh Saurabh, Samarpit Masih

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引用次数: 1

摘要

本文介绍了eKYC (Electronic Know Your Customer)系统的一个模块，该系统使用人脸识别对来自各种数字来源的个人进行身份识别和认证。该方法采用局部二值模式直方图(LBPH)算法来解决人脸识别问题。在光照条件、面部表情、姿态偏转和变换的情况下，识别率会发生变化。该防欺骗系统基于一种基于卷积神经网络(CNN)的架构。该系统的准确率为95%。

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Anti-Spoofing Face-Recognition Technique for eKYC Application

This paper presents a module of eKYC (Electronic Know Your Customer) system using face recognition for identification and authentication of an individual from a variety of digital sources. The proposed method implements the Local Binary Pattern Histogram (LBPH) algorithm to solve the face recognition problem. The recognition rate varies under lighting conditions, facial expression, attitude deflection and transformations. The anti- spoofing system is based on a proposed Convolution Neural Network (CNN) based architecture. The accuracy of the proposed system is 95%.

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2021 3rd International Conference on Signal Processing and Communication (ICPSC)

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