Cross Entropy Clustering Approach to Iris Segmentation for Biometrics Purpose
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RIS BIB ENDNOTECross Entropy Clustering Approach to Iris Segmentation for Biometrics Purpose
Publication date: 11.04.2016
Schedae Informaticae, 2015, Volume 24, pp. 31-40
https://doi.org/10.4467/20838476SI.15.003.3025Authors
Cross Entropy Clustering Approach to Iris Segmentation for Biometrics Purpose
This work presents the step by step tutorial for how to use cross entropy clustering for the iris segmentation. We present the detailed construction of a suitable Gaussian model which best fits for in the case of iris images, and this is the novelty of the proposal approach. The obtained results are promising, both pupil and iris are extracted properly and all the information necessary for human identification and verification can be extracted from the found parts of the iris.
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Information: Schedae Informaticae, 2015, Volume 24, pp. 31-40
Article type: Original article
Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland
Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland
Department of Ophthalmology, Faculty of Medicine, Medical University of Bialystok
Faculty of Computer Science Bialystok University of Technology
Faculty of Mathematics and Computer Science, Jagiellonian University ul. Łojasiewicza 6, 30-348 Kraków, Poland
Published at: 11.04.2016
Article status: Open
Licence: None
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