基于树莓派和物联网的自动柜员机安全用于DSWD 4P的生物识别系统,使用指纹识别与快速傅里叶变换图像增强,多阶段细节提取

Ericson D. Dimaunahan, A. Ballado, F. Cruz
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引用次数: 4

摘要

在自动取款机交易中,盗卡和身份盗窃现象十分普遍。使用通用密码系统和使用指纹作为身份识别,消除了在密码已知的情况下容易发生的卡盗卡和盗窃的情况,加强了当前的ATM交易过程。在自动柜员机进行交易时,来自指纹传感器的图像要经过多个步骤才能提供正确的用户身份识别。研究人员提出了设计一种系统的想法,通过使用每个人都独一无二的指纹识别来消除刷卡和身份盗窃的可能性。该系统采用快速傅里叶变换作为图像处理之一,以产生更好的图像质量,用于细节识别。系统的仿真性能指标显示,系统的FAR和FRR分别为0%和15.79%,准确率为92.11%。图像以无线方式远程传输到远程服务器,实现了完整的物联网,为远程移动ATM设置提供了更好的移动性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Raspberry Pi and IOT Based-Automated Teller Machine Security for the DSWD 4P's Biometric System Using Fingerprint Recognition with Fast- Fourier Transform Image Enhancement, Multi-Stage Minutia Extraction
Card skimming and identity theft in ATMs transactions are prevalent nowadays. The use of the common PIN system together with the use of fingerprint as one's identification, eliminating the card skimming- and theft-prone typical card when the PIN is known, strengthens the current ATM transaction process. Images from fingerprint sensors undergo a multi-step process to provide proper user identification when transacting in ATMs. The researcher came up with the idea of designing a system to eliminate possibilities of card skimming and identity theft with the use of a fingerprint identification which is unique for each person. The system uses Fast Fourier Transform as one of its image process to produce better image quality to be used for minutiae identifications. The system's simulated performance indices showed an FAR and FRR of 0% and 15.79%, respectively, and accuracy of 92.11%. The image is remotely transmitted to a distant server wirelessly, implementing a full Internet of Things providing the system a better mobility for mobile ATM Setups in far places.
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