Biometrics

Retinal vessel tree is a suitable biometric pattern as it’s unique for each individual, it’s very hard to forge and, unless some pathologies arise, it doesn’t change in time. In our group, we have developed an authentication system based on this retinal vessel tree.
We are currently working on the individual characterization based on the feature extraction from the vessel tree. These features are related to the bifurcations or crossings of vessels in the retinal vessel tree. This will allow to build an easily and more robust biometric pattern.

Public databases

VARIA database

The VARIA database is a set of retinal images used for authentication purposes. The database currently includes 233 images, from 139 different individuals. The images have been acquired with a TopCon non-mydriatic camera NW-100 model and are optic disc centered with a resolution of 768×584.

The database distribution includes a directory with the images and a index.txt file indicating which images are from each user.

If you are interested in using the VARIA database, please send an email to: mortega@udc.es and you will receive an authentication password to access the database. This is intended for statistical purposes only, no private data or fee is required. If you use this image set for your works, please include a reference of VARIA in it by citing the original papers where the database was introduced

  • M. Ortega, M. G. Penedo, J. Rouco, N. Barreira, M. J. Carreira, «Retinal verification using a feature points based biometric pattern», EURASIP Journal on Advances in Signal Processing, vol. 2009, Article ID 235746, 13 pp., 2009.
  • M. Ortega, M. G. Penedo, J. Rouco, N. Barreira, M. J. Carreira, «Personal verification based on extraction and characterization of retinal feature points», Journal of Visual Languages and Computing, 20 (2), 80-90, 2009.

Main publications

  • D. Calvo, M. Ortega, M. G. Penedo, J. Rouco, B. Remeseiro, «Characterisation of retinal feature points applied to a biometric system», International Conference on Image Analysis and Processing (ICIAP), 5716, 355-363, 2009.
Abstract
In this work a methodology for the classification of retinal feature points is applied to a biometric system. This system is based in the extraction of feature points, namely bifurcations and crossovers as biometric pattern. In order to compare a pattern to other from a known individual a matching process takes place between both points sets. That matching task is performed by finding the best geometric transform between sets, i.e. the transform leading to the highest number of matched points. The goal is to reduce the number of explored transforms by introducing the previous characterisation of feature points. This is achieved with a constraint avoiding two differently classified points to match. The empirical reduction of transforms is about 20%.
  • M. Ortega, M. G. Penedo, J. Rouco, N. Barreira, M. J. Carreira, «Retinal verification using a feature points based biometric pattern», EURASIP Journal on Advances in Signal Processing, vol. 2009, Article ID 235746, 13 pp., 2009.
Abstract
Biometrics refer to identity verification of individuals based on some physiologic or behavioural characteristics. The typical authentication process of a person consists in extracting a biometric pattern of him/her and matching it with the stored pattern for the authorized user obtaining a similarity value between patterns. In this work an efficient method for persons authentication is showed. The biometric pattern of the system is a set of feature points representing landmarks in the retinal vessel tree. The pattern extraction and matching is described. Also, a deep analysis of similarity metrics performance is presented for the biometric system. A database with samples of retina images from users on different moments of time is used, thus simulating a hard and real environment of verification. Even in this scenario, the system allows to establish a wide confidence band for the metric threshold where no errors are obtained for training and test sets.
  • C. Alonso-Montes, M. Ortega, M. G. Penedo, D. L. Vilarino, «Pixel Parallel Vessel Tree Extraction for a Personal Authentication System», IEEE International Symposium on Circuits and Systems – CIRSYS, 1596-1599, Seattle (USA), 2008.
Abstract
Biometric features have been studied in order to be applied to authentication and identification systems due to its reliability. Among others, the retinal vessel tree have been proposed as a vessel pattern for personal authentication applications, since it is almost impossible to forge. In this kind of systems, the retinal vessel tree is computed from the retinal image, and then a registration process is made. Although reliable and remarkable results have been obtained in this vessel pattern-based system, the required computation effort is quite high, particularly to compute and extract the vessel tree. In this paper, a pixel parallel approach is proposed to tackle with the retinal vessel tree extraction in order to be used in a personal retinal authentication system, regarding the computation speed. An analysis has been made to test the performance of our obtained tree with the original proposal.
  • C. Mariño, M. G. Penedo, M. Penas, M. J. Carreira, F. González, «Personal authentication using digital retinal images», Pattern Analysis and Applications, 9, 21-33, 2006.
Abstract
Traditional authentication (identity verification) systems, employed to gain access to a private area in a building or to data stored in a computer, are based on something the user «has» (an authentication card, a magnetic key) or something the user «knows» (a password, an identification code). But emerging technologies allow for more reliable and comfortable for the user, authentication methods, most of them based in biometric parameters. Much work could be found in literature about biometric based authentication, using parameters like iris, voice, fingerprint, face characteristics, and others. In this work a novel authentication method is presented, and first results obtained are shown. The biometric parameter employed for the authentication is the retinal vessel tree, acquired through a retinal angiography. It has already been asserted by expert clinicians that the configuration of the retinal vessels is unique for each individual and that it does not vary in his life, so it is a very well suited identification characteristic. Before the verification process can be executed, a registration step is needed to align both the reference image and the picture to be verified. A fast and reliable registration method is used to perform that step, so that the whole authentication process takes very little time.