R. Donida Labati, A. Genovese, V. Piuri, F. Scotti, Touchless palmprint and fingerprint recognition, Advances in Computing, Informatics, Networking and Cybersecurity - A Book Honoring Prof. Mohammad S. Obaidat’s Significant Scientific Contributions, Lecture Notes in Networks and Systems, vol. 289, pp. 267-298, Springer, Cham, 2022, ISSN 978-3-030-87049-2.
Biometric systems
Touchless 2D Fingerprint Recognition
Most of the fingerprint recognition systems use touch-based acquisition devices, which suffer from important intrinsic problems, such as non-linear deformations of the captured images, non-uniform contrast of the fingerprint regions, presence of latent fingerprints on the sensor surface, sensibility to dust and dirt, and low social acceptance. Touchless fingerprint recognition systems based on CCD cameras are studied in order to overcome these problems.
With respect to techniques based on three-dimensional models, the studied methods based on a single touchless image have the advantage of requiring low-cost and small hardware setups, which can easily be integrated in mobile devices and consumer applications.
An important characteristic of the studied approaches is that they do not use finger placement guides, reducing the acquisition constraints with respect to most of the contactless fingerprint recognition systems in the literature.
The studied techniques regard different aspects of contactless biometric systems: acquisition, quality evaluation of biometric samples, computation of contact-equivalent images, matching algorithms, and computation of synthetic samples.
With respect to techniques based on three-dimensional models, the studied methods based on a single touchless image have the advantage of requiring low-cost and small hardware setups, which can easily be integrated in mobile devices and consumer applications.
An important characteristic of the studied approaches is that they do not use finger placement guides, reducing the acquisition constraints with respect to most of the contactless fingerprint recognition systems in the literature.
The studied techniques regard different aspects of contactless biometric systems: acquisition, quality evaluation of biometric samples, computation of contact-equivalent images, matching algorithms, and computation of synthetic samples.
Relevant publications
R. Donida Labati, F. Scotti, Fingerprint, Encyclopedia of Cryptography, Security and Privacy, pp. 1--6, Springer Berlin Heidelberg, Berlin, Heidelberg, January 2021, ISSN 978-3-642-27739-9.
R. Donida Labati, A. Genovese, E. Muñoz, V. Piuri, F. Scotti, A novel pore extraction method for heterogeneous fingerprint images using Convolutional Neural Networks, Pattern Recognition Letters, vol. 113, pp. 58-66, October 2018, ISSN 0167-8655.
A. Genovese, E. Muñoz, V. Piuri, F. Scotti, G. Sforza, Towards touchless pore fingerprint biometrics: a neural approach, Proc. of the 2016 IEEE Congress on Evolutionary Computation (CEC 2016), pp. 4265-4272, Vancouver, BC, Canada, July 2016, ISSN 978-1-5090-0623-6.
R. Donida Labati, Contactless Fingerprint Biometrics: Acquisition, Processing, and Privacy Protection, Ph.D. Dissertation, Universita' degli Studi di Milano, Italy, February 2013.
R. Donida Labati, F. Scotti, Fingerprint, Encyclopedia of Cryptography and Security (2nd ed.), pp. 460-465, Springer, 2011, ISSN 978-1-4419-5905-8.
R. Donida Labati, A. Genovese, V. Piuri, F. Scotti, Measurement of the principal singular point in contact and contactless fingerprint images by using computational intelligence techniques, Proc. of the 2010 IEEE Int. Conf. on Computational Intelligence for Measurement Systems and Applications (CIMSA 2010), pp. 18-23, Taranto, Italy, September 2010, ISSN 978-1-4244-7228-4.
R. Donida Labati, V. Piuri, F. Scotti, Neural-based quality measurement of fingerprint images in contactless biometric systems, Proc. of the 2010 IEEE-INNS Int. Joint Conf. on Neural Networks (IJCNN 2010), pp. 1-8, Barcelona, Spain, July 2010, ISSN 978-1-4244-6916-1.
V. Piuri, F. Scotti, Fingerprint biometrics via low-cost sensors and webcams, Proc. of the 2008 IEEE Int. Conf. on Biometrics: Theory, Applications and Systems (BTAS 2008), pp. 1-6, Washington, D.C., USA, September 2008, ISSN 978-1-4244-2729-1.