UBIRIS

UBIRIS: A noisy iris image database. Within the biometrics context, the iris is commonly accepted as one of the most accurate biometric traits and has been successfully applied in such distinct domains as airport check-in or refugee control. However, for the sake of accuracy, present iris recognition systems require that subjects stand close (less than two meters) to the imaging camera and look for a period of about three seconds until the data is captured. This cooperative behavior is required to capture images with enough quality for the recognition task. However, it simultaneously restricts the range of domains where iris recognition can be applied, especially those where the subjects cooperation is not expectable (e.g., criminal/terrorist seek, missing children). The main focus of the UBIRIS database is to minimize the requirement of user cooperation, i.e., the analysis and proposal of methods for the automatic recognition of individuals, using images of their iris captured at-a-distance and minimizing the required degree of cooperation from the users, probably even in the covert mode.


References in zbMATH (referenced in 8 articles )

Showing results 1 to 8 of 8.
Sorted by year (citations)

  1. Efimov, Yu. S.; Leonov, V. Yu.; Odinokikh, G. A.; Solomatin, I. A.: Finding the iris using convolutional neural networks (2021)
  2. Zainulina, E. T.; Matveev, I. A.: Binding cryptographic keys into biometric data: optimization (2020)
  3. Gankin, K. A.; Gneushev, A. N.; Matveev, I. A.: Iris image segmentation based on approximate methods with subsequent refinements (2014)
  4. Mat Raffei, Anis Farihan; Asmuni, Hishammuddin; Hassan, Rohayanti; Othman, Razib M.: Fusing the line intensity profile and support vector machine for removing reflections in frontal RGB color eye images (2014) ioport
  5. Rahulkar, Amol D.; Waghmare, Laxman M.; Holambe, Raghunath S.: A new approach to the design of hybrid finer directional wavelet filter bank for iris feature extraction and classification using (k)-out-of-(n:A) post-classifier (2014) ioport
  6. Mat Raffei, Anis Farihan; Asmuni, Hishammuddin; Hassan, Rohayanti; Othman, Razib M.: Feature extraction for different distances of visible reflection iris using multiscale sparse representation of local Radon transform (2013) ioport
  7. Matveev, I. A.: Iris center location using Hough transform with two-dimensional parameter space (2012) ioport
  8. Matveev, I. A.: Circular shortest path as a method of detection and refinement of iris borders in eye image (2011) ioport


Further publications can be found at: http://iris.di.ubi.pt/publications.html