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Iris Codes Classification Using Discriminant and Witness Directions

Domenii publicaţii > Ştiinţe informatice + Tipuri publicaţii > Articol în volumul unei conferinţe

Autori: N. Popescu-Bodorin, V.E. Balas, I.M. Motoc

Editorial: IEEE Press, Proc. 5th IEEE Int. Symp. on Computational Intelligence and Intelligent Informatics, p.143-148, 2011.

Rezumat:

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 distributions 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.

Cuvinte cheie: iris recognition, formal theories of iris recognition, discriminant and witness direction, iris codes classification // iris recognition, formal theories of iris recognition, discriminant and witness direction, iris codes classification

URL: http://fmi.spiruharet.ro/bodorin/articles/2011-fm-bodorin-balas-motoc-2.pdf