Face Authentication System Embedded with PIC18F458 for Automated Teller Machines

Choodarathnakara A L,Karibasappa R,Rashmi M Hullamani,Sushma S

doi:10.37314/jjem.2020.040203

Abstract

Face recognition system is one of the biometric information process. Its applicability is easier and working range is wider than other biometric systems like signature, fingerprint, iris, etc. This paper proposes, a face recognition based authentication scheme for automated teller machine banking systems. The designed detection method extract face features from input image. The output image of the face detection algorithm has to be similar with the input image recognized for successful authentication. The proposed PIC18F458 Microcontroller based face recognition biometric scheme is successfully fused with the automated teller machine banking system for personal authorization with increased social security.

Highlights

Due to rapid development in science and technology, upcoming innovations are being built up with strong security
This paper proposes, a face recognition based authentication scheme for automated teller machine banking systems
The proposed PIC18F458 Microcontroller based face recognition biometric scheme is successfully fused with the automated teller machine banking system for personal authorization with increased social security

Summary

Introduction

Due to rapid development in science and technology, upcoming innovations are being built up with strong security. On the other hand, threats are being posed to destroy this security level. The existing ATM model uses a card and a PIN which gives rise to increase in attacks in the form of stolen cards, or due to statically assigned PINs, duplicity of cards and various other threats [1], [2]. Automatic retraction of forgotten card or cash by ATMs is a problem with serious consequences (lost time and money), typically caused by user inattention or negligence. This proposes a scheme in which the retraction rate of an ATM is decreased using face detection and recognition methods via ATMs built-in camera [3]

Objectives

Results

Conclusion