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Iris Recognition: On the Segmentation of Degraded Images Acquired in the Visible Wavelength
August 2010 (vol. 32 no. 8)
pp. 1502-1516
ASCII Text
x 
 
Hugo Proença, "Iris Recognition: On the Segmentation of Degraded Images Acquired in the Visible Wavelength," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 8, pp. 1502-1516, August, 2010.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2009.140,
author = {Hugo Proença},
title = {Iris Recognition: On the Segmentation of Degraded Images Acquired in the Visible Wavelength},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {32},
number = {8},
issn = {0162-8828},
year = {2010},
pages = {1502-1516},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2009.140},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Iris Recognition: On the Segmentation of Degraded Images Acquired in the Visible Wavelength
IS - 8
SN - 0162-8828
SP1502
EP1516
EPD - 1502-1516
A1 - Hugo Proença,
PY - 2010
KW - Iris segmentation
KW - biometrics
KW - noncooperative image acquisition
KW - visible-light iris images
KW - covert recognition.
VL - 32
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
Hugo Proença, Universidad da Beira Interior, Covilhã
Iris recognition imaging constraints are receiving increasing attention. There are several proposals to develop systems that operate in the visible wavelength and in less constrained environments. These imaging conditions engender acquired noisy artifacts that lead to severely degraded images, making iris segmentation a major issue. Having observed that existing iris segmentation methods tend to fail in these challenging conditions, we present a segmentation method that can handle degraded images acquired in less constrained conditions. We offer the following contributions: 1) to consider the sclera the most easily distinguishable part of the eye in degraded images, 2) to propose a new type of feature that measures the proportion of sclera in each direction and is fundamental in segmenting the iris, and 3) to run the entire procedure in deterministically linear time in respect to the size of the image, making the procedure suitable for real-time applications.

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Index Terms:
Iris segmentation, biometrics, noncooperative image acquisition, visible-light iris images, covert recognition.
Citation:
Hugo Proença, "Iris Recognition: On the Segmentation of Degraded Images Acquired in the Visible Wavelength," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 8, pp. 1502-1516, Aug. 2010, doi:10.1109/TPAMI.2009.140
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