Liveness Detection with Opencv
C. Anuradha1, R. Kavitha2, A.V.Allin Geo3, S. R. Srividhya4
1C. Anuradha, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, India.
2R. Kavitha, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, India.
3A.V.Allin Geo Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai , India.
4S. R.Srividhya, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai , India.
Manuscript received on 04 July 2019 | Revised Manuscript received on 17 July 2019 | Manuscript Published on 23 August 2019 | PP: 583-585 | Volume-8 Issue-9S3 August 2019 | Retrieval Number: I31160789S319/2019©BEIESP | DOI: 10.35940/ijitee.I3116.0789S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Biometric system is widely used to recognize the authorized person based on either behavioural characteristics or physical. But this can be spoofed using various traits. Spoofing attack is nothing but attacking or harming biometric recognition system using security features to use system without permission of authorized user. Images or video of person can be easily available from social media or can be easily captured from some distance. Consider what would happen if a nefarious user tried to purposely circumvent your face recognition system. Such a user could try to hold up a photo of another person. Maybe they even have a photo or video on their smart phone that they could hold up to the camera responsible for performing face recognition .In the project, we have tried spotting these “fake” versus “real/legitimate” faces and how we could apply anti-face spoofing algorithms into our facial recognition applications by applying live ness detection[1] with Open CV.
Keywords: Biometric System, Optical Flow Algorithms, Local Binary Patterns(LBP)
Scope of the Article: Algorithm Engineering