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Experiments with an Improved Iris Segmentation Algorithm
Buffalo, New York October 17-October 18
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AUTOID.2005.21Fourth IEEE Workshop on Automatic Ide ...
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Xiaomei Liu, Kevin W. Bowyer, Patrick J. Flynn, "Experiments with an Improved Iris Segmentation Algorithm," Automatic Identification Advanced Technologies, IEEE Workshop on, pp. 118-123, Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID'05), 2005.
 
 
BibTex
x
 
@article{ 10.1109/AUTOID.2005.21,
author = {Xiaomei Liu and Kevin W. Bowyer and Patrick J. Flynn},
title = {Experiments with an Improved Iris Segmentation Algorithm},
journal ={Automatic Identification Advanced Technologies, IEEE Workshop on},
volume = {0},
year = {2005},
isbn = {0-7695-2475-3},
pages = {118-123},
doi = {http://doi.ieeecomputersociety.org/10.1109/AUTOID.2005.21},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Automatic Identification Advanced Technologies, IEEE Workshop on
TI - Experiments with an Improved Iris Segmentation Algorithm
SN - 0-7695-2475-3
SP118
EP123
A1 - Xiaomei Liu,
A1 - Kevin W. Bowyer,
A1 - Patrick J. Flynn,
PY - 2005
KW - null
VL - 0
JA - Automatic Identification Advanced Technologies, IEEE Workshop on
ER -
 
Xiaomei Liu, University of Notre Dame
Kevin W. Bowyer, University of Notre Dame
Patrick J. Flynn, University of Notre Dame
Iris is claimed to be one of the best biometrics. We have collected a large data set of iris images, intentionally sampling a range of quality broader than that used by current commercial iris recognition systems. We have re-implemented the Daugman-like iris recognition algorithm developed by Masek. We have also developed and implemented an improved iris segmentation and eyelid detection stage of the algorithm, and experimentally verified the improvement in recognition performance using the collected dataset. Compared to Masek?s original segmentation approach, our improved segmentation algorithm leads to an increase of over 6% in the rank-one recognition rate.
Citation:
Xiaomei Liu, Kevin W. Bowyer, Patrick J. Flynn, "Experiments with an Improved Iris Segmentation Algorithm," autoid, pp.118-123, Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID'05), 2005
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