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Vascular patterns, as formed by the blood vessel structure inside the human body, are used in biometrics to identify a human individual. The corresponding field in biometrics is thus termed “vascular biometrics” (Uhl et al. 2019; Uhl 2019) or “vascular recognition”. The following eye-based biometric modalities are typically classified into this trait category: Retina recognition (Mazumdar and Nirmala 2018) and sclera recognition (Das et al. 2013).
The vascular patterns have to be made visible and captured by a suitable biometric scanner device in order to use them to conduct biometric recognition. Both retina recognition as well as sclera recognition operate in the visible wavelength domain (VIS), however, the illumination requirements are fairly different.While being rather unproblematic for sclera recognition, imaging the retinal vascular network is accomplished...
References
Alkassar S, Woo W, Dlay S, Chambers J (2017) Sclera recognition: on the quality measure and segmentation of degraded images captured under relaxed imaging conditions. IET Biometrics 6(4):266–275
Das A, Pal U, Blumenstein M, Ballester MAF (2013) Sclera recognition - a survey. In: Second IAPR Asian Conference on Pattern Recognition (ACPR’13), pp 917–921
Das S, Malathy C (2018) Survey on diagnosis of diseases from retinal images. Journal of Physics: Conference Series 1000(1):012,053
Elhussieny N, El-Rewaidy H, Fahmy AS (2016) Low cost system for screening cardiovascular diseases in large population: preliminary results. In: 13th International IEEE Symposium on Biomedical Imaging (ISBI’18)
Haddock L, Qian C (2015) Smartphone technology for fundus photography. Retinal Physician 12(6):51–58
Jeffers J, Arakala A, Horadam KJ (2010) Entropy of feature point-based retina templates. In: 20th International Conference on Pattern Recognition (ICPR’10), pp 213–216, doi: https://doi.org/10.1109/ICPR.2010.61
Jini K, Lu H, Sun Z, Cheng C, Ye J, Qian D (2017) Telemedicine screening of retinal diseases with a handheld portable non-mydriatic fundus camera. BMC Ophthalmology 17:89
Khanamiri HN, Nakatsuka A, El-Annan J (2017) Smartphone fundus photography. Journal of Visualised Experiments 125:55,958
Lin SJ, Yang CM, Yeh PT, Ho TC (2014) Smartphone fundoscopy for retinopathy of prematurity. Taiwan Journal of Ophthalmology 4(2):82 – 85
Maamari RN, Keenan J, Fletcher DA, Margolis T (2014) A mobile phone-based retinal camera for portable wide field imaging. The British Journal of Ophthalmology 98:438–441
Mazumdar JB, Nirmala SR (2018) Retina based biometric authentication system: A review. International Journal of Advanced Research in Computer Science 9(1)
Miri M, Amini Z, Rabbani H, Kafieh R (2017) A comprehensive study of retinal vessel classification methods in fundus images. Journal of Medical Signals and Sensing 7(2):59–70
Swedish T, Roesch K, Lee I, Rastogi K, Bernstein S, Raskar R (2015) eyeselfie: Self directed eye alignment using reciprocal eye box imaging. ACM Trans Graph 34(4)
Uhl A (2019) State of the art in vascular biometrics. In: Uhl A, Busch C, Marcel S, Veldhuis R (eds) Handbook of Vascular Biometrics, Springer Nature Switzerland AG, Cham, Switzerland, chap 1, pp 3 – 61, doi: https://doi.org/10.1007/978-3-030-27731-4
Uhl A, Busch C, Marcel S, Veldhuis R (2019) Handbook of Vascular Biometrics. Advances in Computer Vision and Pattern Recognition, Springer Nature Switzerland AG, Cham, Switzerland, doi: https://doi.org/10.1007/978-3-030-27731-4
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Uhl, A. (2021). Eye-based Vascular Patterns. In: Jajodia, S., Samarati, P., Yung, M. (eds) Encyclopedia of Cryptography, Security and Privacy. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27739-9_1738-1
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DOI: https://doi.org/10.1007/978-3-642-27739-9_1738-1
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