3 research outputs found
Exploratory simulation of an Intelligent Iris Verifier Distributed System
This paper discusses some topics related to the latest trends in the field of
evolutionary approaches to iris recognition. It presents the results of an
exploratory experimental simulation whose goal was to analyze the possibility
of establishing an Interchange Protocol for Digital Identities evolved in
different geographic locations interconnected through and into an Intelligent
Iris Verifier Distributed System (IIVDS) based on multi-enrollment. Finding a
logically consistent model for the Interchange Protocol is the key factor in
designing the future large-scale iris biometric networks. Therefore, the
logical model of such a protocol is also investigated here. All tests are made
on Bath Iris Database and prove that outstanding power of discrimination
between the intra- and the inter-class comparisons can be achieved by an IIVDS,
even when practicing 52.759.182 inter-class and 10.991.943 intra-class
comparisons. Still, the test results confirm that inconsistent enrollment can
change the logic of recognition from a fuzzified 2-valent consistent logic of
biometric certitudes to a fuzzified 3-valent inconsistent possibilistic logic
of biometric beliefs justified through experimentally determined probabilities,
or to a fuzzified 8-valent logic which is almost consistent as a biometric
theory - this quality being counterbalanced by an absolutely reasonable loss in
the user comfort level.Comment: 4 pages, 2 figures, latest version: http://fmi.spiruharet.ro/bodorin
Iris Codes Classification Using Discriminant and Witness Directions
The main topic discussed in this paper is how to use intelligence for
biometric decision defuzzification. A neural training model is proposed and
tested here as a possible solution for dealing with natural fuzzification that
appears between the intra- and inter-class distribution of scores computed
during iris recognition tests. It is shown here that the use of proposed neural
network support leads to an improvement in the artificial perception of the
separation between the intra- and inter-class score distributions by moving
them away from each other.Comment: 6 pages, 5 figures, Proc. 5th IEEE Int. Symp. on Computational
Intelligence and Intelligent Informatics (Floriana, Malta, September 15-17),
ISBN: 978-1-4577-1861-8 (electronic), 978-1-4577-1860-1 (print