N. Fakhraei, R. Donida Labati, V. Piuri, F. Scotti, Iris Super-Resolution for Images Sourced from Websites and Social Media, Proceedings of the Joint National Conference on Cybersecurity (ITASEC & SERICS 2026), Cagliari, Italy, February 2026.
Biometric systems
Unconstrained Iris Recognition
Some biometric traits can be captured by using technologies that does not require the contact of the user with a sensor. Theoretically, it is possible to design biometric systems that capture these traits without subjects' knowledge and in uncontrolled scenarios. This type of biometric systems should be useful in different applicative scenarios (e.g. police investigations, surveillance, etc.). In this context, iris is one of the most interesting biometric traits, since iris recognition systems are one of the most accurate biometric techniques. The behavior of most traditional iris segmentation algorithms is designed for controlled/low-noise environments and it is typically not satisfactory in noisy images, where specific methods are needed to successfully cope with this peculiar applicative contest. The work we propose deals with the segmentation of the iris patterns in this type of noisy images.
Relevant publications
Donida Labati, Ruggero, Piuri, Vincenzo, Scotti, Fabio, Iris Recognition from Websites and Social Media: State of the Art and Privacy Concerns, Security and Cryptography, Springer Nature Switzerland, Cham, 2026, ISSN 978-3-032-09598-5.
N. Fakhraei, R. Donida Labati, V. Piuri, F. Scotti, Deep Learning-based Iris Quality Assessment for Images Sourced from Websites and Social Media, 2025 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), Piraeus, Greece, June 2025, ISSN 979-8-3315-2436-4.
R. Donida Labati, V. Piuri, F. Rundo, F. Scotti, Iris Reflection Segmentation from Ocular Images Acquired in Uncontrolled and Uncooperative Conditions, 2023 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), pp. 1-6, June 2023.
R. Donida Labati, A. Genovese, V. Piuri, F. Scotti, S. Vishwakarma, I-SOCIAL-DB: A labeled database of images collected from websites and social media for iris recognition, Image and Vision Computing, vol. 105, no. 104058, pp. 1-9, January 2021, ISSN 0262-8856.
M. Barni, R. Donida Labati, A. Genovese, V. Piuri, F. Scotti, Iris deidentification with high visual realism for privacy protection on websites and social networks, IEEE Access, vol. 9, pp. 131995-132010, 2021, ISSN 2169-3536.
R. Donida Labati, E. Muñoz, V. Piuri, A. Ross, F. Scotti, Non-ideal iris segmentation using Polar Spline RANSAC and illumination compensation, Computer Vision and Image Understanding, vol. 188, Elsevier, November 2019, ISSN 1077-3142.
R. Donida Labati, A. Genovese, V. Piuri, F. Scotti, Iris segmentation: state of the art and innovative methods, Cross Disciplinary Biometric Systems, Intelligent Systems Reference Library, vol. 37, pp. 151-182, Springer Berlin Heidelberg, 2012, ISSN 978-3-642-28457-1.
F. Scotti, V. Piuri, Adaptive reflection detection and location in iris biometric images by using computational intelligence techniques, IEEE Transactions on Instrumentation and Measurement, vol. 59, no. 7, pp. 1825-1833, July 2010, ISSN 0018-9456.
R. Donida Labati, F. Scotti, Noisy iris segmentation with boundary regularization and reflections removal, Image and Vision Computing, Iris Images Segmentation Special Issue, vol. 28, no. 2, pp. 270 - 277, Elsevier, February 2010, ISSN 0262-8856.
R. Donida Labati, V. Piuri, F. Scotti, Agent-based image iris segmentation and multiple views boundary refining, Proc. of the 2009 IEEE Int. Conf. on Biometrics: Theory, Applications and Systems (BTAS 2009), pp. 1-7, Washington, D.C., USA, September 2009, ISSN 978-1-4244-5019-0.
R. Donida Labati, V. Piuri, F. Scotti, Neural-based iterative approach for iris detection in iris recognition systems, Proc. of the IEEE Symp. on Computational Intelligence for Security and Defence Applications (CISDA 2009), pp. 1-6, Ottawa, ON, Canada, July 2009, ISSN 978-1-4244-3763-4.
F. Scotti, Computational intelligence techniques for reflections identification in iris biometric images, Proc. of the 2007 IEEE Int. Conf. on Computational Intelligence for Measurement Systems and Applications (CIMSA 2007), pp. 84-88, Ostuni, Italy, June 2007, ISSN 978-1-4244-0824-5.
N. Fakhraei, R. Donida Labati, V. Piuri, F. Scotti, Deepfakes in Iris Recognition: A Preliminary Study on Synthetic Ocular Images from Web and Social Media, Proceedings of the European Signal Processing Conference (EUSIPCO), 2026, ACCEPTED.