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Title: :  Liveness Verification for Face Recognition System
PaperId: :  19941
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 2 2023
DUI:    16.0415/IJARIIE-19941
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Sarvesh Harish ChaudhariSinhgad College of Engineering, Pune
Abhirav Suneel GoteSinhgad College of Engineering, Pune
Sayed Faizan Masood KadriSinhgad College of Engineering, Pune
Samruddhi Sukdev GadakhSinhgad College of Engineering, Pune
Prof. Ankita A. KotalwarSinhgad College of Engineering, Pune

Abstract

Computer Engineering
Face Recognition, Computer Vision, Image Analysis, Spoofing Attack, Face Liveness Verification, CNN
The popularity of face recognition is increasing due to its ability to recognize human faces, making it a popular topic for computer vision research. Despite its usefulness in image analysis and understanding, face recognition systems face challenges with fraudulent identities, commonly known as spoofing attacks. To address this challenge, face liveness detection is an important biometric authentication method that distinguishes between authentic and fake faces. Liveness detection can be implemented using software or hardware means. However, the use of additional hardware can be costly. The project aims to develop a liveness verification system for face recognition that can accurately distinguish between live and spoofed faces. Spoofing attacks on face recognition systems are becoming increasingly common, and therefore, it is necessary to develop robust liveness verification techniques. The proposed system employs a combination of physiological and behavioral biometric modalities to detect fake faces, including eye blinking, head movement, and facial expressions. The system also utilizes machine learning algorithms to analyze and classify live and spoofed faces based on various features extracted from the biometric data. The effectiveness of the proposed system is evaluated using a large dataset of live and spoofed faces, and the results show a high accuracy in detecting fake faces. The developed liveness verification system has the potential to improve the security of face recognition systems and prevent unauthorized access to sensitive information. Therefore, this paper proposes a CNN-based model for liveness verification and a web-based application to demonstrate its real-time implementation.

Citations

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IJARIIE Sarvesh Harish Chaudhari, Abhirav Suneel Gote, Sayed Faizan Masood Kadri, Samruddhi Sukdev Gadakh, and Prof. Ankita A. Kotalwar. "Liveness Verification for Face Recognition System" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 2 2023 Page 2865-2872
MLA Sarvesh Harish Chaudhari, Abhirav Suneel Gote, Sayed Faizan Masood Kadri, Samruddhi Sukdev Gadakh, and Prof. Ankita A. Kotalwar. "Liveness Verification for Face Recognition System." International Journal Of Advance Research And Innovative Ideas In Education 9.2(2023) : 2865-2872.
APA Sarvesh Harish Chaudhari, Abhirav Suneel Gote, Sayed Faizan Masood Kadri, Samruddhi Sukdev Gadakh, & Prof. Ankita A. Kotalwar. (2023). Liveness Verification for Face Recognition System. International Journal Of Advance Research And Innovative Ideas In Education, 9(2), 2865-2872.
Chicago Sarvesh Harish Chaudhari, Abhirav Suneel Gote, Sayed Faizan Masood Kadri, Samruddhi Sukdev Gadakh, and Prof. Ankita A. Kotalwar. "Liveness Verification for Face Recognition System." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 2 (2023) : 2865-2872.
Oxford Sarvesh Harish Chaudhari, Abhirav Suneel Gote, Sayed Faizan Masood Kadri, Samruddhi Sukdev Gadakh, and Prof. Ankita A. Kotalwar. 'Liveness Verification for Face Recognition System', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 2, 2023, p. 2865-2872. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Liveness_Verification_for_Face_Recognition_System_ijariie19941.pdf (Accessed : 30 May 2024).
Harvard Sarvesh Harish Chaudhari, Abhirav Suneel Gote, Sayed Faizan Masood Kadri, Samruddhi Sukdev Gadakh, and Prof. Ankita A. Kotalwar. (2023) 'Liveness Verification for Face Recognition System', International Journal Of Advance Research And Innovative Ideas In Education, 9(2), pp. 2865-2872IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Liveness_Verification_for_Face_Recognition_System_ijariie19941.pdf (Accessed : 30 May 2024)
IEEE Sarvesh Harish Chaudhari, Abhirav Suneel Gote, Sayed Faizan Masood Kadri, Samruddhi Sukdev Gadakh, and Prof. Ankita A. Kotalwar, "Liveness Verification for Face Recognition System," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 2, pp. 2865-2872, Mar-App 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/Liveness_Verification_for_Face_Recognition_System_ijariie19941.pdf [Accessed : 30 May 2024].
Turabian Sarvesh Harish Chaudhari, Abhirav Suneel Gote, Sayed Faizan Masood Kadri, Samruddhi Sukdev Gadakh, and Prof. Ankita A. Kotalwar. "Liveness Verification for Face Recognition System." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 2 (30 May 2024).
Vancouver Sarvesh Harish Chaudhari, Abhirav Suneel Gote, Sayed Faizan Masood Kadri, Samruddhi Sukdev Gadakh, and Prof. Ankita A. Kotalwar. Liveness Verification for Face Recognition System. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : 30 May 2024]; 9(2) : 2865-2872. Available from: https://ijariie.com/AdminUploadPdf/Liveness_Verification_for_Face_Recognition_System_ijariie19941.pdf
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