[09-17]sdd edd-identity verification providers

SYSTEMS AND METHODS OF ILLUMINATION CONTROL FOR BIOMETRIC CAPTURE AND LIVENESS DETECTION

Date:2021-09-17

aml in kyc

Author:mlro in banking    digital identity use cases

Keywords:cip aml kyc,    electronic identity check,    kyc procedures,    verify someone's identity,    customer id verification,  amla checklist

Description:

Android-Based Liveness Detection for Access Control in Smart Homes
Liveness check through measuring synchrony between the lip and the voice in video sequence has been proved to be a feasible way to prevent spoofing attacks. The generic methods utilize degree of audiovisual correlation to judge consistency. However, little attention is paid to the audiovisual time drift difference between live recordings and fraudulent attacks. In this paper, the time shift difference and the delay range is concluded by delay estimation experiments on VidTIMID. According to the conclusion, we propose an improved liveness scores evaluation algorithm for audio-video identification system. Experimental results on the same database show that the proposed algorithm got better performance. In comparison with the traditional methods, the EER (Equal Error Rate) averagely decreases about 5%.
Biometrics represents a return to a traditional way of identifying someone relying on what that person is instead of what that person knows or owns. Even though the significant amount of research that has been done in this field, there is still much to do as new emerging scenarios of application appear everyday. Biometric recognition systems are no longer restricted to forensic investigation or control management of employees. They have been gaining a visibility and applicability in daily use devices which reinforces their usability in all aspects of our day to day life. With this spread of biometric applications, nowadays commonly found in our laptops, our smart phones, some bank management services and airport custom services, a necessity for improved security also is rising. The importance of protecting our identity and our data has become crucial as our devices are filled with sensible information of many kinds. Therefore the presentation attack or liveness detection methods as countermeasures against spoofing attacks are more important than ever. New methods should be developed which address the new acquisition scenarios and which deal with the increased noise in the biometric data collected. Its of utmost importance to develop robust liveness detection methods. In particular, we worked on iris and fingerprint. These two biometric traits are very often chosen against others due to its characteristics. Among the objectives of this thesis were the purpose of making contributions in iris and fingerprint liveness detection proposing novel approaches whether from the imaging scenarios perspective, in the case of iris, or from the classification approach, in the case of fingerprint. Contributions were made regarding both traits, that exceeded the state-of-the art and resulted in both conferences and journal publications. Not only the spoofing attacks concern the biometric researchers but also the ability of the methods to deal with the noisy data. Therefore, the development of robust methods that overcome the compromised quality of data is a necessity of biometric research of nowadays. Therefore, another objective was to contribute to the fingerprint recognition problem developing robust methods to minutiae extraction. The work developed resulted in a proposed method for fingerprint orientation map estimation and a fingerprint image enhancement that over performed existing ones. This work aimed and succeeded to propose robust and realistic methods in both the iris and fingerprint liveness detection problem as well as in some steps of fingerprint recognition. It has to be noted that the focus of attention of this work was the quality of data and not the computational efficiency, therefore this one should have to be addressed if an application of the proposed methods to a real-world scenario was aimed. Another objective was to create new databases and promote common platforms of evaluation of methods such as biometric competitions. Therefore, along the work developed, two biometric databases were constructed and two biometric competitions were organized. Both databases had a strong impact in the research community and they continue to be disseminated. Publications using these benchmark datasets are numerous and continue to appear regularly.

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