Open AccessFINGERPRINT AND FACE RECOGNITION BASED ATM SYSTEM USING RASPBERRY PI
Author(s) -
S Kavyashree,
AUTHOR_ID,
M Supreetha,
AUTHOR_ID
Publication year - 2021
Publication title -
international journal of innovative research in advanced engineering
Language(s) - English
Resource type - Journals
ISSN - 2349-2163
DOI - 10.26562/ijirae.2021.v0807.008
Subject(s) - fingerprint (computing) , biometrics , computer security , facial recognition system , smart card , computer science , face (sociological concept) , identification (biology) , database transaction , fingerprint recognition , fingerprint verification competition , atm card , matching (statistics) , internet privacy , artificial intelligence , pattern recognition (psychology) , world wide web , database , social science , botany , sociology , biology , statistics , mathematics , payment
ATMs (Automatic Teller Machine) are becoming widely used in today's world because they are easy to use and offer convenience. However, today's ATM technology comes with some security risks such as the theft and misuse of cards, the possibility of losing a card, and forgetting PIN numbers. A growing number of frauds committed against automatic teller machines over the last decade motivated us to use biometrics to ensure the accuracy and security of personal identification. In this paper, we describe a biometric fingerprint and face recognition system that can replace ATM cards and PINs. The transaction is successful when fingerprint, OTP, and face match. If the fingerprint does not match, the customer is guided to enter the aadhaar number. Similarly, if face matching fails, the customer is given an option to answer the question. Here aadhaar number and correct answer to the question must be entered correctly to proceed. Aadhaar number entry and question & answer options are mainly provided for those who are unable to access the system because of damage to their physical attributes (finger and face).