An Improved Iris Recognition System Based on Possibilistic Modeling-Reference-Cited by-同舟云学术

An Improved Iris Recognition System Based on Possibilistic Modeling

Published:2015-12-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 13th International Conference on Advances in Mobile Computing and Multimedia
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Author:

Bellaaj Majd¹,Elleuch Jihen Frikha²,Sellami Dorra²,Kallel Imen Khanfir³

Affiliation:

1. Sfax University, National Engineering School of Sfax, CEM laboratory, BP W, 3038 Sfax, Tunisia, +21622617461

2. Sfax University, National Engineering School of Sfax, CEM laboratory, BP W, 3038 Sfax, Tunisia

3. Sfax University, National Engineering School of Sfax, BP W, 3038 Sfax, Tunisia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2837126.2837156

Reference25 articles.

1. Robust and accurate iris segmentation in very noisy iris images

2. Moi S.H. Asmuni H. Hassan R. Othman R.M. 2014. Multimodal biometrics: Weighted score level fusion based on non-ideal iris and face images. Published in Elsevier journal of Expert Systems with Applications. Moi S.H. Asmuni H. Hassan R. Othman R.M. 2014. Multimodal biometrics: Weighted score level fusion based on non-ideal iris and face images. Published in Elsevier journal of Expert Systems with Applications.

3. Smets P. 1996. Imperfect information: Imprecision and uncertainty. Published in Kluwer Academic book of Uncertainty Management in Information Systems pp. 225--254 Boston. Smets P. 1996. Imperfect information: Imprecision and uncertainty. Published in Kluwer Academic book of Uncertainty Management in Information Systems pp. 225--254 Boston.

4. Zadeh L.A. 1965. Fuzzy sets Information and Control. 8 338--353. Zadeh L.A. 1965. Fuzzy sets Information and Control. 8 338--353.

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2. Probability/Possibility Systems for Modeling of Random/Fuzzy Information with Parallelization Consideration;International Journal of Fuzzy Systems;2019-04-02