BACKGROUND: Biometric methods are security technologies, which use human characteristics for personal identification. Iris recognition systems use iris textures as unique identifiers. This paper presents an analysis of the verification of iris identities after intra-ocular procedures, when individuals were enrolled before the surgery. METHODS: Fifty-five eyes from fifty-five patients had their irises enrolled before a cataract surgery was performed. They had their irises verified three times before and three times after the procedure, and the Hamming (mathematical) distance of each identification trial was determined, in a controlled ideal biometric environment. The mathematical difference between the iris code before and after the surgery was also compared to a subjective evaluation of the iris anatomy alteration by an experienced surgeon. RESULTS: A correlation between visible subjective iris texture alteration and mathematical difference was verified. We found only six cases in which the eye was no more recognizable, but these eyes were later reenrolled. The main anatomical changes that were found in the new impostor eyes are described. CONCLUSIONS: Cataract surgeries change iris textures in such a way that iris recognition systems, which perform mathematical comparisons of textural biometric features, are able to detect these changes and sometimes even discard a pre-enrolled iris considering it an impostor. In our study, re-enrollment proved to be a feasible procedure

Allen L Ronald

Fabio Dante

J Daugman

Jaime Roizenblatt

JG Daugman

NS Jaffe

Paulo Schor

Roberto Roizenblatt

Rubens Belfort

S Nanavati

English

PubMed

Abstract
              
                Background
                Biometric methods are security technologies, which use human characteristics for personal identification. Iris recognition systems use iris textures as unique identifiers. This paper presents an analysis of the verification of iris identities after intra-ocular procedures, when individuals were enrolled before the surgery.
              
              
                Methods
                Fifty-five eyes from fifty-five patients had their irises enrolled before a cataract surgery was performed. They had their irises verified three times before and three times after the procedure, and the Hamming (mathematical) distance of each identification trial was determined, in a controlled ideal biometric environment. The mathematical difference between the iris code before and after the surgery was also compared to a subjective evaluation of the iris anatomy alteration by an experienced surgeon.
              
              
                Results
                A correlation between visible subjective iris texture alteration and mathematical difference was verified. We found only six cases in which the eye was no more recognizable, but these eyes were later reenrolled. The main anatomical changes that were found in the new impostor eyes are described.
              
              
                Conclusions
                Cataract surgeries change iris textures in such a way that iris recognition systems, which perform mathematical comparisons of textural biometric features, are able to detect these changes and sometimes even discard a pre-enrolled iris considering it an impostor. In our study, re-enrollment proved to be a feasible procedure

Roizenblatt, Roberto

Schor, Paulo

Dante, Fabio

Roizenblatt, Jaime

Belfort, Rubens

Universidade de São Paulo

Iris recognition as a biometric method after cataract surgery

Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)

Abstract\ud
              \ud
                Background\ud
                Biometric methods are security technologies, which use human characteristics for personal identification. Iris recognition systems use iris textures as unique identifiers. This paper presents an analysis of the verification of iris identities after intra-ocular procedures, when individuals were enrolled before the surgery.\ud
              \ud
              \ud
                Methods\ud
                Fifty-five eyes from fifty-five patients had their irises enrolled before a cataract surgery was performed. They had their irises verified three times before and three times after the procedure, and the Hamming (mathematical) distance of each identification trial was determined, in a controlled ideal biometric environment. The mathematical difference between the iris code before and after the surgery was also compared to a subjective evaluation of the iris anatomy alteration by an experienced surgeon.\ud
              \ud
              \ud
                Results\ud
                A correlation between visible subjective iris texture alteration and mathematical difference was verified. We found only six cases in which the eye was no more recognizable, but these eyes were later reenrolled. The main anatomical changes that were found in the new impostor eyes are described.\ud
              \ud
              \ud
                Conclusions\ud
                Cataract surgeries change iris textures in such a way that iris recognition systems, which perform mathematical comparisons of textural biometric features, are able to detect these changes and sometimes even discard a pre-enrolled iris considering it an impostor. In our study, re-enrollment proved to be a feasible procedure

Crossref

Springer - Publisher Connector

BioMed CentralBioMedical Engineering OnLine
ssOpen AcceResearch
Iris recognition as a biometric method after cataract surgery
Roberto Roizenblatt*1, Paulo Schor1, Fabio Dante1, Jaime Roizenblatt2 and 
Rubens Belfort Jr1
Address: 1Department of Ophthalmology, Federal University of Sao Paulo-Vision Institute, Sao Paulo, Brazil and 2Department of Ophthalmology, 
University of Sao Paulo, Sao Paulo, Brazil
Email: Roberto Roizenblatt* - rrtt@uol.com.br; Paulo Schor - pschor@pobox.com; Fabio Dante - fadante@zipmail.com.br; 
Jaime Roizenblatt - jroizenb@usp.br; Rubens Belfort - eyebr@webmail.epm.br
* Corresponding author    
identification of personsiris recognitionpattern recognitioncataract surgery
Abstract
Background: Biometric methods are security technologies, which use human characteristics for
personal identification. Iris recognition systems use iris textures as unique identifiers. This paper
presents an analysis of the verification of iris identities after intra-ocular procedures, when
individuals were enrolled before the surgery.
Methods: Fifty-five eyes from fifty-five patients had their irises enrolled before a cataract surgery
was performed. They had their irises verified three times before and three times after the
procedure, and the Hamming (mathematical) distance of each identification trial was determined,
in a controlled ideal biometric environment. The mathematical difference between the iris code
before and after the surgery was also compared to a subjective evaluation of the iris anatomy
alteration by an experienced surgeon.
Results: A correlation between visible subjective iris texture alteration and mathematical
difference was verified. We found only six cases in which the eye was no more recognizable, but
these eyes were later reenrolled. The main anatomical changes that were found in the new
impostor eyes are described.
Conclusions: Cataract surgeries change iris textures in such a way that iris recognition systems,
which perform mathematical comparisons of textural biometric features, are able to detect these
changes and sometimes even discard a pre-enrolled iris considering it an impostor. In our study,
re-enrollment proved to be a feasible procedure.
Background
Biometrics is the automated use of physiological or
behavioral characteristics to determine or verify identity.
Biometric authentication requires only a few seconds, and
biometric systems are able to compare thousands of
records per second. Finger-scan, facial-scan, iris-scan,
hand-scan and retina-scan are considered physiological
biometrics and voice-scan and signature-scan are consid-
ered behavioral biometrics. A distinction may be drawn
between an individual and an identity; the individual is
singular, but he may have more than one identity, for
Published: 28 January 2004
BioMedical Engineering OnLine 2004, 3:2
Received: 14 November 2003
Accepted: 28 January 2004
This article is available from: http://www.biomedical-engineering-online.com/content/3/1/2
© 2004 Roizenblatt et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in 
all media for any purpose, provided this notice is preserved along with the article's original URL.Page 1 of 7
(page number not for citation purposes)
BioMedical Engineering OnLine 2004, 3 http://www.biomedical-engineering-online.com/content/3/1/2example ten registered fingerprints are viewed as ten dif-
ferent identities [1].
The combinatorial complexity of phase information
across different iris textures from persons spans around
249 degrees of freedom and generates discrimination
entropy of about 3.2 bits/mm2 over the iris, enabling deci-
sions about personal identity with extremely high confi-
dence[2]. The extracted feature is the phase characteristic
of the picture element in study, related to adjacent ones,
in an infrared (not color) iris photograph. This means, for
example, that false match probabilities might be as low as
one in 1074. False reject rates may be as high as 5–10%
depending on ambient conditions, so scientific tests
should be done under ideal conditions to minimize
chance for errors.
The matching process is as follows: a user initially enrolls
in biometric systems by providing biometric data, which
are converted into a template. Templates are small
archives called "iris codes" (Figure 1), consisting of opti-
mized and filtered biometric acquired images. These tem-
plates are stored in biometric systems for the purpose of
sub sequential comparison. Then the user presents his
biometric data again, and another template is created. The
verification template is compared to the enrollment tem-
plate, and the mathematical difference between the iris
codes is computed. This mathematical difference is called
the Hamming distance (HD) [4]. In other words, the
Hamming distance is the numerical difference between
two iris codes. The Hamming distance between identifica-
tion and enrollment codes is used as a score and is com-
pared to a confidence threshold for a specific equipment
or use, giving a match or non-match result. Systems may
be highly secure or not secure, depending on their confi-
dence threshold settings.
Iris code from an iris-scanF gure 1
Iris code from an iris-scan. (Adapted from [3] (© 1990 IEEE))Page 2 of 7
(page number not for citation purposes)
BioMedical Engineering OnLine 2004, 3 http://www.biomedical-engineering-online.com/content/3/1/2Data acquisition begins with reliable means of establish-
ing a visible iris, and then its boundaries are precisely
located by a circular edge detector algorithm. Extracting
textural characteristics are based in 2-D Gabor phasor
coefficients which are computed, providing high orienta-
tional and spatial-frequency resolution as well as the
information of its 2-D position. Zones of analysis are
established on the iris in a projected polar coordinate sys-
tem, dimensionless, in order to maintain reference to the
same regions of the iris regardless of constriction of iris
(pupillary size), distance to eye and video zoom factor.
Each bit in an iris code can be regarded as a coordinate of
a vertice in a unit square of the complex plane from the
coordinate system described above, forming a 256 bytes
code, which is used for comparisons [5].
The decision made by the algorithm may be either correct
or incorrect. The four outcomes, as illustrated above, are
consequently a correct accept, false accept, correct reject
and false reject. Figure 2 illustrates the idea of a decision
environment in a recognition system. The two distribu-
tions represent the two statuses, authentic and impostor,
which are imperfectly separated. The abscissa is a metric of
similarity, the Hamming distance. In this case, a 0.4 HD
criterion best separates the two distributions of patterns
[6].
Unique templates are generated every time a user presents
biometric data, due to changes in positioning, distance,
pressure, environment and other factors. Data from real
comparisons using iris recognition systems in laboratory
conditions (at a single illuminance, with well-informed
volunteers) reveal more distant curves, which do not over-
lap (Figure 3) [5-9].
General formalism for biometric decision makingFigure 2
General formalism for biometric decision making (Adapted from [6] (© 1999 IEEE))Page 3 of 7
(page number not for citation purposes)
BioMedical Engineering OnLine 2004, 3 http://www.biomedical-engineering-online.com/content/3/1/2The equipment is also able to rotate the images and com-
pensate for tilt and pupillary dilation.
There are, to our knowledge, no scientific papers describ-
ing medical procedures interfering in biometric data in
iris recognition, there are reports in fingerprinting though
[10]. The aim of this study was to verify what could hap-
pen to recognition capacity when a common intra-ocular
procedure such as cataract surgery alters iris texture [11],
and what kind of misrecognition could take place.
Methods
We report data from fifty-five patients chosen for cataract
surgery performed by second year residents in their first
semester of phacoemulsification training. From the 55
patients, 28 right cataractous eyes and 27 left cataractous
eyes were selected, although we know an iris from a per-
sons' eye is as much different from the contralateral eye as
it is from another persons' [3]. The Iris Recognition Sys-
tem used had its reproducibility validated by the licensees
of the algorithms and the equipment used in the study is
LG's IrisAccess 2000®. Informed consent was gathered
from each patient and the protocol was approved by the
ethics committee of the Federal University of São Paulo.
Patients were properly positioned in front of the equip-
ment and maximum ocular opening was instructed.
Research was conducted in the same room under constant
illuminance (horizontal and vertical 70 lux) and at fixed
distance to the equipment, so that ideal laboratory condi-
tions (described in [2]) were accomplished. The iris was
separated in four quadrants and these were photographed
with a slit lamp-attached Topcon® camera. All patients had
never undergone any other ocular surgery and did not
have other associated ocular diseases. Enrollment was fol-
lowed by three identification trials, and Hamming dis-
Decision environment for iris recognition under ideal laboratory conditionsFigure 3
Decision environment for iris recognition under ideal laboratory conditions (Adapted from [5] (© 1993 IEEE))Page 4 of 7
(page number not for citation purposes)
BioMedical Engineering OnLine 2004, 3 http://www.biomedical-engineering-online.com/content/3/1/2tance and focus data were retrieved. Three trials were not
necessary giving the favorable experiment conditions, but
sometimes old patients sneeze or cough and move aside
from the equipment, so we chose the best trial in three.
The patient then underwent the operation. One month
after the procedure, and one week after the use of mydri-
atics was discontinued; each patient was subjected to three
identification trials. Pupillary size changes were
accounted for in the algorithm, and we describe that none
of our patients were dilated and we could not see pupil-
lary size differences larger than 1.5 mm. The major iris
changes occur in the first postoperative period due to sur-
gical manipulation, and the acute healing with the
chronic tissue retraction are usually complete by one
month, hence the testing period length. Hamming dis-
tance and focus were retrieved and slit-lamp photographs
were taken. At this time, each patient had his or her iris
examined in the slit-lamp by an anterior segment special-
ist, who gave a score for the visible texture alterations. One
point was given for each of the following alterations: focal
atrophy without transillumination, depigmentation, focal
atrophy with transillumination and pupil ovalization. A
score of zero represented no visible alterations and a score
of four meant all of these visible alterations were present.
The average preoperative Hamming distance was then
compared to the average postoperative Hamming dis-
tance. The threshold determined for the Hamming dis-
tance was 0.4, the same used in most indoors public
applications. The Hamming distance difference between
the lowest postoperative and preoperative distance was
then calculated for each case. The lowest value was chosen
because it corresponds to the best image acquisition for
coding purposes. The score created for each patient's clin-
ical alterations was then compared to the numeric differ-
ence for each case, so that a relationship between clinical
visible textural alterations and numeric difference could
be established.
The end points of the analysis were assessed with the use
of SPSS software; analysis of variance and Students' t test
were used to test for statistical significance.
Results
All image captures were suitable for optimal image acqui-
sition, with a good focus values over 95% (up to 100%
scale, acceptable if over 70%) and image quality values
over 1200 (up to 1600 specific scale, acceptable if over
600). In all cases there was a correspondence between
maximum ocular opening achieved in the preoperative
and postoperative period, as verified in the pictures cap-
tured at the moment of iris codes determination.
Six patients were no longer recognized (example at Figure
4) after the procedure, and these eyes were reenrolled cre-
ating a new template or iris code. All other patients were
still recognized even though they had numerical and clin-
ical alterations.
The average of Hamming distances in the preoperative
period was 0.098 and in the postoperative period it was
0.2094; the numeric overall difference is 11.13%.
The patients were divided into three groups for statistical
purposes: Scores = zero, Scores = 1 and Scores > 1. For
each of these groups the number of patients (n), average
difference in Hamming distance (avg) and pattern devia-
tion (pd) were as follows: Score = zero group had n = 13,
avg = 0.0696, pd = 0.0604; Score = 1 group had n = 24, avg
= 0.0840, pd = 0.0611; Score > 1 group had n = 18, avg =
0.178, pd: 0.120. Using ANOVA for group comparison we
found there were statistically significant differences
between the groups (p < 0.001). There were statistically
significant differences between groups Score = 1 and Score
> 1 (p < 0.05) and Score = 0 and Score > 1 (p < 0.05), but
no difference between groups Score = 0 and Score = 1(p <
0.05) (Tukey test).
Discussion
All surgeries were performed by residents in phacoemulsi-
fication, under the tutelage of an experienced surgeon.
Consequently this study does not intend and does not
actually reproduce iris alterations at a rate similar to the
usual ophthalmologic practice. All patients in this study
had a proper interaction with the system as it was carefully
explained how the image capture procedure works and
they were cooperative. The mechanism of iris change due
to the probe is usually unknown, though it is known that
iris tissue can be emulsified when the probe tip is pointed
to it and there is progressive atrophy after manipulation;
it is speculated that even without any contact with the iris
tissue, the energy dissipated in the anterior chamber
might be responsible for depigmentation.
The mean Hamming distance changed 11.3% during the
study due to the surgical procedure, from 0.098 to 0.2094;
in other words, the authentics' curve moved into the
threshold direction (and the direction of the impostors'
curve) by 11.13%. That move is not big enough for most
individuals, who were still recognized.
Repetitive individual iris scanning under non ideal condi-
tions of an unoperated eye should not find differences in
more than 10% of the iris code, and usually less than 5%.
The mathematical difference association with visible slit-
lamp textural alterations indicates that there is a positive
association between the procedure and an outside normal
iris code variation. It also indicates that we are able to pre-
dict cases in which iris recognition systems will have diffi-
culty identifying people based on slit-lamp examinations.Page 5 of 7
(page number not for citation purposes)
BioMedical Engineering OnLine 2004, 3 http://www.biomedical-engineering-online.com/content/3/1/2The most common iris changes were depigmentation and
localized iris atrophy, with loss of large areas of Fuchs'
crypts, circular and radial furrows and pupil ovalization.
In this study there were no false matches, in other words,
no patient was identified as another individual because of
his textural changes. To sum up we understand some
patients can be identified successfully and others cannot
due to the existence of a damage threshold, yet to be deter-
mined, which is correlated with the degree of visible
changes and we propose the iris biometric reenrollment
of all patients submitted to cataract surgery, in order to
avoid false negative results in pseudophakic patient iris
identification. Iris specific alterations correspondence in
the code appears to be one of the probable natural
sequences for our research.
Conclusion
Cataract procedures are able to change iris texture in such
a way that iris pattern recognition is no longer feasible or
the probability of false rejected subjects is increased.
Patients who are subjected to intraocular procedures may
be advised to reenroll in biometric iris systems which use
this particular algorithm so as to have a new template in
the database.
Authors' contributions
RR carried out the iris analysis and drafted the manuscript.
PS conceived the sequential idea of the study. FD took all
iris color photographs. JR participated in the sequence
alignment. RBJ participated in its design and
coordination.
Color and infrared photos of a patient before and after the cataract surgeryFigu e 4
Color and infrared photos of a patient before and after the cataract surgery Same iris, before and after surgery. (A 
and B) Color photos. (C and D) Infrared photos of subject A and B (E and F) Barely visible changes. Score 0. (G and H) Light 
depigmentation. Score 1.
A B
C D
EPage 6 of 7
(page number not for citation purposes)
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Acknowledgments
To Fapesp, grant #0147-6/02 and LG Electronics.
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Iris recognition as a biometric method after cataract surgery

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