Logo des Repositoriums

Auflistung nach Autor:in "Ramachandra, Raghavendra"

1 - 5 von 5
  • Konferenzbeitrag
    Biometric Transaction Authentication using Smartphones
    (BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group, 2018) Stokkenes, Martin; Ramachandra, Raghavendra; Busch, Christoph
    Secure and robust authentication of users and customers is critical, as an increasing number of services from banks, health and government sectors are made available to people as online services. Recent development in the area of biometrics, e.g. biometric systems in smartphones, has contributed to higher adoption of the technology as a viable authentication factor in modern systems. In this work, we propose an approach for authenticating transactions in an online bank by using a combination of Bloom filters and error correcting codes. Firstly, protected biometric templates, using Bloom filters, are generated from faces detected in images captured using smartphones. Secondly, a key, shared between a smartphone and a bank server, is encoded using error correcting codes. The encoded key is then secured in the smartphone using the protected biometric templates. Authentication of a banking transaction is realised by unlocking the secured key with a protected biometric template that is close to the template used to lock the key. Experiments are performed on a database consisting of images and videos captured using an iPhone 6S.
  • Konferenzbeitrag
    Cross-eyed - cross-spectral iris/periocular recognition database and competition
    (Biosig 2016, 2016) Sequeira, Ana F.; Chen, Lulu; Ferryman, James; Alonso-Fernandez, Fernando; Bigun, Josef; Raja, Kiran B.; Ramachandra, Raghavendra; Busch, Christoph; Wild, Peter
  • Konferenzbeitrag
    Fake Face Detection Methods: Can They Be Generalized?
    (BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group, 2018) Khodabakhsh, Ali; Ramachandra, Raghavendra; Raja, Kiran; Wasnik, Pankaj; Busch, Christoph
    With advancements in technology, it is now possible to create representations of human faces in a seamless manner for fake media, leveraging the large-scale availability of videos. These fake faces can be used to conduct personation attacks on the targeted subjects. Availability of open source software and a variety of commercial applications provides an opportunity to generate fake videos of a particular target subject in a number of ways. In this article, we evaluate the generalizability of the fake face detection methods through a series of studies to benchmark the detection accuracy. To this extent, we have collected a new database of more than 53;000 images, from 150 videos, originating from multiple sources of digitally generated fakes including Computer Graphics Image (CGI) generation and many tampering based approaches. In addition, we have also included images (with more than 3;200) from the predominantly used Swap-Face application that is commonly available on smart-phones. Extensive experiments are carried out using both texture-based handcrafted detection methods and deep learning based detection methods to find the suitability of detection methods. Through the set of evaluation, we attempt to answer if the current fake face detection methods can be generalizable.
  • Konferenzbeitrag
    Improved Fingerphoto Verification System Using Multi-scale Second Order Local Structures
    (BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group, 2018) Wasnik, Pankaj; Ramachandra, Raghavendra; Stokkenes, Martin; Raja, Kiran; Busch, Christoph
    Today’s high-end smartphones are embedded with advanced fingerprint biometric recognition systems that require dedicated sensors to capture the fingerprint data. The inclusion of such sensors helps in achieving better biometric performance and hence can enable various applications that demand reliable identity verification. However, fingerphoto recognition systems have some inherent advantages over fingerprint recognition such as no latent fingerprints, and it enables the possibility to capture multiple samples at once from a biometric instance with minimal user interaction. Thus, user authentication based on fingerphotos could be a useful alternative as we can re-use the smartphone camera to capture the fingerphotos. On the other hand, such an approach introduces different challenges; for example illumination, orientation, background variation, and focus resulting in lower biometric performance. In this research, we propose a novel verification framework based on the feature extracted from the eigenvalues of convolved images using multi-scale second order Gaussian derivatives. The proposed framework is used to authenticate individuals based on images/ videos of their fingers captured using the built-in smartphone cameras. When combining with the commercial off the shelf (COTS) system, the proposed feature extraction technique has achieved the improved verification performance with an equal error rate of 2:76%.
  • Konferenzbeitrag
    Smartphone Authentication System Using Periocular Biometrics
    (BIOSIG 2014, 2014) Raja, Kiran B.; Ramachandra, Raghavendra; Stokkenes, Martin; Busch, Christoph
    The increasing usage of smartphones has raised security concerns regarding these devices due to presence of high amount of personal and sensitive data. The risk is higher without a proper mechanism to handle the authentication to access the smartphone device. In this work, we present a standalone modular biometric system based on periocular information to authenticate towards device. The proposed system has been implemented on the Android operating system. We field tested and evaluated the proposed system using a new database acquired capturing samples with three different devices. We apply the three well known feature extraction techniques, SIFT, SURF and BSIF independently in the proposed peroicular based authentication system. The best performance achieved with GM R = 89.38\% at F M R = 0.01\% indicates the applicability of the proposed periocular based mobile authentication system in a reallife scenario.