Improve ATM Security by Face Recognition

1369 Words3 Pages

Abstract- In this paper the method face Recognition is using to access Automated teller machines (ATMs). ATMs are used to do banking function like checking balance withdraw money, changing pin numbers etc. The ATM cards and pin numbers are used for security purpose. But this system is using SIM card in place of ATM cards. In order to improve security the system first authenticate the person if he/she is recognized then it will ask the password of the account. This system used Spartan 3 FPGA board to control the system. One buzzer is connected on the FPGA board which gives instructions to the user to access the Account. If the person is not authenticated then the process is terminated and the output is show on FPGA board with the help of LEDs.

Keywords- Recognition, ATM, PCA, GSM, FPGA, Euclidian distance

I. INTRODUCTION

The face recognition plays very important role in security system [4]. The main objective of face recognition is to recognize person from pictures or video using databases of face. There are a lots of variation to design a face recognition is not an easy task [2]. Due to variation in illumination, facial expression and poses variations it is difficult to do face recognition [7]. A number of defense , security and commercial application demand real time face recognition system, especially when other biometric technique are not feasible [1]. In this paper the system is using face recognition to access the ATM. Automated teller machines (ATMs) are used by user to do banking function like withdraw money, checking balance etc. In these days ATMs are very popular because it works all days of the week and it provides 24 hours service. We can find ATMs anywhere in cities, railway stations, near societies, near restauran...

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...otani, Feifei Lee and Tadahiro Ohmi,” Face Recognition Using Self-Organizing Maps” www.intechopen.com

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[7] Mohammed Alwakeel , Zyad Shaaban ,”Face Recognition Based on Haar Wavelet Transform and Principal Component Analysis via Levenberg-Marquardt Backpropagation Neural Network” in European Journal of Scientific Research,2010 pp. 25-31

[8] Kyungnam Kim, “Face Recognition using Principle Component”, Analysis” www.google.com

[9] Kyungnam Kim, “Face Recognition using Principle Component”, Analysis” www.google.com

[10] Lindsay I Smith, “A tutorial on Principal Components Analysis” February 26, 2002

[11] www.mathwork.com

[12] www.google.com

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