Multiresolution Deep Learning Based Touchless Biometrics

By Prof. Vikram Gadre


The field of biometrics and security is a study of unique physical or behavioral traits of humans, which can be used for various applications: such as person identification, authentication, forensics, border security, attendance systems and so on. There still exist a number of problems/challenges in this field, which need to be addressed. We have addressed some of these problems: mainly deformation invariant classification of a large scale fingerprint database, touchless fingerprint recognition, scattering network for ear recognition, phase encoding of iris recognition and enhancement of latent fingerprints on banknotes. In particular, we have developed a novel algorithm for fingerprint classification, based on scattering wavelet networks, to extract translation and small deformation invariant local features. This is an example of an approach, which unifies multiresolution principles with deep learning. Automatic ear recognition system uses ear images, that are obtained from video footages or profile headshots. The process of acquisition of ear images is also nonintrusive, contactless and does not require much co-operation from the subject. The shape, structure and appearance of ears is unique and invariant to ageing. Our approach, which employs multiresolution deep learning is also useful here. A latent fingerprint on banknotes can be very useful information for law enforcement agencies, in identifying criminals in bank robbery and counterfeiters. Due to the complex background of a banknote, it is extremely challenging not only to automatic two-fingerprint matchers, but also for fingerprint experts. We have some preliminary work on analyzing latent fingerprints, which we shall briefly outline.


Vikram M. Gadre is a Professor in the Department of Electrical Engineering at IIT Bombay. His main areas of research include multiresolution and multi-rate signal processing, wavelets, and allied areas. He has a number of publications in reputed journals and conferences in this area. In addition to the regular academic courses, taught as a part of his duties as a faculty member at IIT Bombay, Dr.Gadre has made a number of efforts to organize and participate in continuing education programs for the industry and for other research organizations. Dr.Gadre has been the recipient of the “Award for excellence in teaching at IIT Bombay” in the years 1999, 2004, 2009, and 2014. He has also been awarded the prestigious Indian National Science Academy (INSA) Teachers’ Award in December 2017. Apart from academic and research activities, Dr.Gadre has also served as a reviewer, for a number of IEEE Journals and other journals of international/ national repute. Over the years, Dr.Gadre has pursued many projects in collaboration with the industry and government organizations alike. Sagar Sangodkar is an erstwhile M. Tech. Student of the Department of Electrical Engineering, IIT Bombay, who worked with Prof. Gadre’s supervision for his Masters’ Dissertation (Project). He graduated with an M. Tech. Degree in 2020, with an excellent academic record and has been associated with NCETIS throughout his project duration.

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