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Joint Austrian Computer Vision and Robotics Workshop 2020
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[3] ISO/IEC JTC1 SC37 Biometrics. ISO/IEC IS 19795-1:2006, it – Biometric performance testing and reporting–Part1: Principles and framework. [4] ISO/IECJTC1SC37Biometrics. ISO/IECIS30107- 1:2016, IT–Biometricpresentationattackdetection –Part1: Framework. [5] ISO/IECJTC1SC37Biometrics. ISO/IECIS30107- 3:2017, IT–Biometricpresentationattackdetection –Part3: TestingandReporting. [6] C. Kauba, B. Prommegger, and A. Uhl. Focus- sing the beam - a new laser illumination based data set providing insights to finger-vein recognition. In 2018 IEEE 9th Int. Conference on Biometrics The- ory,ApplicationsandSystems(BTAS),LosAngeles, California,USA, 2018. [7] C. Kauba, B. Prommegger, and A. Uhl. Openvein - an open-source modular multipurpose finger vein scanner design. In A. Uhl, C. Busch, S. Marcel, andR.Veldhuis, editors,HandbookofVascularBio- metrics, chapter3.SpringerNatureSwitzerlandAG, Cham,Switzerland, 2019. [8] C. Kauba and A. Uhl. Shedding light on the veins - reflected lightor transillumination inhand-vein re- cognition. In Proceedings of the 11th IAPR/IEEE Int.ConferenceonBiometrics(ICB’18),GoldCoast, Queensland,Australia, 2018. [9] C.KaubaandA.Uhl. Anavailableopen-sourcevein recognitionframework. InA.Uhl,C.Busch,S.Mar- cel, and R. Veldhuis, editors, Handbook of Vascular Biometrics, chapter 4. Springer Nature Switzerland AG,Cham,Switzerland,2019. [10] D.Kocher,S.Schwarz,andA.Uhl. Empiricalevalu- ationof lbp-extensionfeatures forfingerveinspoof- ingdetection. In2016Int.Conferenceof theBiomet- ricsSpecial InterestGroup (BIOSIG). IEEE, 2016. [11] A. Kumar and Y. Zhou. Human identification us- ing finger images. Image Processing, IEEE Trans- actionson, 21(4), 2012. [12] B. Maser, D. Söllinger, and A. Uhl. Prnu-based detection of finger vein presentation attacks. In 20197thInt.WorkshoponBiometricsandForensics (IWBF), 2019. [13] A. Mittal, A. K. Moorthy, and A. C. Bovik. No- reference image quality assessment in the spatial domain. IEEE Transactions on image processing, 21(12), 2012. [14] N.Miura,A.Nagasaka,andT.Miyatake. Extraction of finger-vein patterns using maximum curvature points in image profiles. IEICE transactions on in- formationandsystems, 90(8), 2007. [15] B. Mythily and K. Sathyaseelan. Measuring the quality of image for fake biometric detection: ap- plication to finger vein. In National conference on research advances in communication, compu- tation, electrical science and structures (NCRAC- CESS), 2015. [16] D. T. Nguyen, Y. H. Park, K. Y. Shin, S. Y. Kwon, H. C. Lee, and K. R. Park. Fake finger-vein image detection based on fourier and wavelet transforms. DigitalSignalProcessing, 23(5), 2013. [17] D. T. Nguyen, H. S. Yoon, T. D. Pham, and K. R. Park. Spoof detection for finger-vein recognition system usingnir camera. Sensors, 17(10), 2017. [18] X. Qiu, W. Kang, S. Tian, W. Jia, and Z. Huang. Finger vein presentation attack detection using total variation decomposition. IEEE Transactions on In- formationForensicsand Security, 13(2), 2017. [19] R. Raghavendra, M. Avinash, S. Marcel, and C. Busch. Finger vein liveness detection using mo- tion magnification. In 2015 IEEE 7th Int. Confer- ence on Biometrics Theory, Applications and Sys- tems (BTAS). IEEE,2015. [20] R. Raghavendra and C. Busch. Presentation attack detection algorithms for finger vein biometrics: A comprehensive study. In 2015 11th Int. Conference on Signal-Image Technology & Internet-Based Sys- tems (SITIS). IEEE,2015. [21] A. F. Sequeira, J. Ferryman, L. Chen, C. Galdi, J.-L. Dugelay, V. Chiesa, A. Uhl, B. Prommegger, C. Kauba, S. Kirchgasser, A. Grudzien, M. Kow- alski, L. Szklarski, P. Maik, and P. Gmitrowicz. PROTECT Multimodal DB: a multimodal biomet- rics dataset envisaging border control. In Proceed- ingsof the Int.Conferenceof theBiometricsSpecial Interest Group (BIOSIG’18), Darmstadt, Germany, 2018. [22] D. Söllinger, P. Trung, and A. Uhl. Non-reference image quality assessment and natural scene statist- ics to counter biometric sensor spoofing. IET Bio- metrics, 7(4), 2018. [23] S. Tirunagari, N. Poh, M. Bober, and D. Windridge. Windowed dmd as a microtexture descriptor for fin- ger vein counter-spoofing in biometrics. In 2015 IEEE Int. Workshop on Information Forensics and Security (WIFS). IEEE,2015. [24] P. Tome and S. Marcel. On the vulnerability of palm vein recognition to spoofing attacks. In The 8th IAPR Int. Conference on Biometrics (ICB), May 2015. [25] P. Tome, R. Raghavendra, C. Busch, S. Tirunagari, N. Poh, B. Shekar, D. Gragnaniello, C. Sansone, L. Verdoliva, and S. Marcel. The 1st competition on counter measures to finger vein spoofing attacks. In 2015 Int. Conference on Biometrics (ICB). IEEE, 2015. [26] P. Tome, M. Vanoni, and S. Marcel. On the vul- nerability of finger vein recognition to spoofing. In IEEE Int. Conference of the Biometrics Special In- terestGroup (BIOSIG), Sept. 2014. [27] A.Uhl,C.Busch,S.Marcel,andR.Veldhuis. Hand- bookof vascularbiometrics. Springer, 2020. 70
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Joint Austrian Computer Vision and Robotics Workshop 2020
Titel
Joint Austrian Computer Vision and Robotics Workshop 2020
Herausgeber
Graz University of Technology
Ort
Graz
Datum
2020
Sprache
englisch
Lizenz
CC BY 4.0
ISBN
978-3-85125-752-6
Abmessungen
21.0 x 29.7 cm
Seiten
188
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Joint Austrian Computer Vision and Robotics Workshop 2020