@inproceedings{436ac053d2cc4b6a996976b54d84265b,
title = "Clever use of Meyer wavelet for iris recognition",
abstract = "An iris recognition requires parametric modeling texture. The extracted model should characterize the individual corresponding to considered iris. Such a model is often referred to as biometric signature. Several approaches to uniquely specify an iris by extracting parameters characteristic of its texture exist in the literature. An original approach based on an analysis by the Meyer wavelet of the iris texture is detailed in this paper. A comparative study between our approach and some techniques that have been studied, implemented and tested in subsequent work is carried out on the CASIA V.1 database. The experimental results show that the proposed method has promising performances.",
keywords = "Biometry, decision, evaluation, iris, Meyer wavelet, texture analysis",
author = "Kallel, \{Imene Khanfir\} and Bouhamed, \{Sonda Ammar\} and Belhassen Akrout",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017 ; Conference date: 22-05-2017 Through 24-05-2017",
year = "2017",
month = oct,
day = "19",
doi = "10.1109/ATSIP.2017.8075515",
language = "English",
series = "Proceedings - 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Hamida, \{Ahmed Ben\} and Basel Solaiman and Slima, \{Ahmed Ben\} and \{El Hassouni\}, Mohammed and Mohammed Karim",
booktitle = "Proceedings - 3rd International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2017",
address = "United States",
}