Article: Face recognition-based security system for automated teller machine using deep face model Journal: International Journal of Medical Engineering and Informatics (IJMEI) 2025 Vol.17 No.3 pp.292 - 299 Abstract: The purpose of this study is to show about using OpenCV and deep learning techniques to design and implement a face recognition-based ATM security system. Face recognition only provides service to the user if the user is authentic or if the user has been validated by an authentic ATM card user. Users are authenticated by comparing the person's video taken in front of the ATM. The proposed method identifies the right persons by comparing the blink of eyes. If someone enters the ATM with photocopy of another person, checking the blink of eyes the validation is made. If the user is authentic, to strengthen the model's accuracy, the current image is being utilised. A web link is sent to the registered mobile number that owns the ATM card, to verify the access of the illegitimate user to his/her account only then the user is considered as a legitimate user. Histogram algorithms and deep learning approaches are used by the system to identify persons. To process the image and detect the faces in the image, this system use the OpenCV package. Face recognition is achieved through the use of an open CV and deep learning. Inderscience Publishers - linking academia, business and industry through research

Title: Face recognition-based security system for automated teller machine using deep face model

Authors: K. Kavin Kumar; S. Mythili; S. Prabhu Kumar

Addresses: Department of Electronics and Communication Engineering, Kongu Engineering College, Erode, Tamil Nadu, India ' Software Developer, Cognizant Technologies Solutions, Plot # 26, Ish Info tech, Rajiv Gandhi Infotech Park, MIDC, Phase I, Hinjawadi, Pune, Maharashtra 411057, India ' Department of Electronics and Communication Engineering, Vel Tech Multi Dr.Rangarajan Dr. Sakunthala Engineering College, Chennai, India

Abstract: The purpose of this study is to show about using OpenCV and deep learning techniques to design and implement a face recognition-based ATM security system. Face recognition only provides service to the user if the user is authentic or if the user has been validated by an authentic ATM card user. Users are authenticated by comparing the person's video taken in front of the ATM. The proposed method identifies the right persons by comparing the blink of eyes. If someone enters the ATM with photocopy of another person, checking the blink of eyes the validation is made. If the user is authentic, to strengthen the model's accuracy, the current image is being utilised. A web link is sent to the registered mobile number that owns the ATM card, to verify the access of the illegitimate user to his/her account only then the user is considered as a legitimate user. Histogram algorithms and deep learning approaches are used by the system to identify persons. To process the image and detect the faces in the image, this system use the OpenCV package. Face recognition is achieved through the use of an open CV and deep learning.

Keywords: OpenCV; blink of eyes; VGG face model; deep face.

DOI: 10.1504/IJMEI.2025.145855

International Journal of Medical Engineering and Informatics, 2025 Vol.17 No.3, pp.292 - 299

Received: 24 Dec 2021
Accepted: 10 Sep 2022
Published online: 30 Apr 2025 *

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Title: Face recognition-based security system for automated teller machine using deep face model

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