@InProceedings{ClimentBlanHexs:2010:ApStMa,
author = "Climent, Joan and Blanco, Juan Diego and Hexsel, Roberto",
affiliation = "{Universitat Polit{\`e}cnica de Catalunya} and {Universitat
Polit{\`e}cnica de Catalunya} and {Universidade Federal do
Paran{\'a}}",
title = "Approximate string matching for iris recognition by means of
boosted Gabor wavelets",
booktitle = "Proceedings...",
year = "2010",
editor = "Bellon, Olga and Esperan{\c{c}}a, Claudio",
organization = "Conference on Graphics, Patterns and Images, 23. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "iris recognition, AdaBoost, biometrics, Levenshtein distance,
string matching.",
abstract = "This paper presents an efficient IrisCode classifier, built from
phase features which uses AdaBoost for the selection of Gabor
wavelets bandwidths. The final iris classifier consists of a
weighted contribution of weak classifiers. As weak classifiers we
use 3-split decision trees that identify a candidate based on the
Levenshtein distance between phase vectors of the respective iris
images. Our experiments show that the Levenshtein distance has
better discrimination in comparing IrisCodes than the Hamming
distance. Our process also differs from existing methods because
the wavelengths of the Gabor filters used, and their final weights
in the decision function, are chosen from the robust final
classifier, instead of being fixed and/or limited by the
programmer, thus yielding higher iris recognition rates. A
pyramidal strategy for cascading filters with increasing
complexity makes the system suitable for realtime operation.",
conference-location = "Gramado, RS, Brazil",
conference-year = "30 Aug.-3 Sep. 2010",
doi = "10.1109/SIBGRAPI.2010.14",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2010.14",
language = "en",
ibi = "8JMKD3MGPBW34M/3886QRE",
url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3886QRE",
targetfile = "Climent.pdf",
urlaccessdate = "2024, May 03"
}