(Fall 2012) The Effects of User Characteristics on Iris Capture

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International Center for Biometric Research

The purpose of this study was to determine if there was an impact on iris capture error rates based on various demographic groups. The three demographics which we explored in our analysis were gender, age and height. We noticed that gender and age showed significant differences in error rates. However height appeared to have no impact on error rates.

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THE EFFECTS OF USER CHARACTERISTICS ON IRIS CAPTURE
The purpose of this study was to determine if there was an impact on iris capture error rates based on various
demographic groups. The three demographics which we explored in our analysis were gender, age and height. We
noticed that gender and age showed significant differences in error rates. However height appeared to have no
impact on error rates.
Michael Porter, Andrew Strong, Mark Haworth, Michael Brockly, Stephen Elliott
Overview
Subject Pool
Gender Age
Height (in inches)
45
53
Male
Female
34
35
15
15 18-24
25-35
36-50
51-69
We used the Tukey range test to determine if there is
significant statistical correlation between demographic group
characteristics. Based on error rates, characteristics were
assigned to a group (A or B) to denote if they are statistically
different or similar. P values were less than .05 for all tables.
We found there was significant difference in error rates
between men and women overall.
We also determined that older age groups show significantly
more errors. The 51-69 age group showed very high error rates
as compared to the other groups.
We looked at the data broken down by age for each gender.
We noticed that the greatest gap of failure rates occurred in
the youngest age group (18-24). In this group, women failed
significantly more often.
We found that differences in height played no distinguishable
role in the number of errors.
Gender N Mean (Failure Rate) Grouping
F 53 8.679 A
M 45 5.044 B
Age N Mean (Failure Rate) Grouping
51-69 15 12.133 A
36-50 15 8 A B
25-35 35 4.686 B
18-24 34 6.529 B
Gender
(18-24 year olds)
N Mean (Failure
Rate)
Grouping
F 20 9.050 A
M 14 2.929 B
Results
This is an overview of the whole
population in our data set
based on age and gender. It is
clear that age does play a role
in error rates. However a larger
population could produce
different results.
It is clear from this chart that
there is no significant
correlation between height and
failure rates.
Final Thoughts
• Further studies with larger populations are necessary to verify our findings.
• A follow up study could be performed to determine if other factors affect these error rates. These factors
could include weight, environment, or test administrator.
Failure Rate Scatter Plots
35%
39%
26% 61-65
66-71
72-79
69 Subjects with and an
average height of 67.8”

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(Fall 2012) The Effects of User Characteristics on Iris Capture

1. THE EFFECTS OF USER CHARACTERISTICS ON IRIS CAPTURE The purpose of this study was to determine if there was an impact on iris capture error rates based on various demographic groups. The three demographics which we explored in our analysis were gender, age and height. We noticed that gender and age showed significant differences in error rates. However height appeared to have no impact on error rates. Michael Porter, Andrew Strong, Mark Haworth, Michael Brockly, Stephen Elliott Overview Subject Pool Gender Age Height (in inches) 45 53 Male Female 34 35 15 15 18-24 25-35 36-50 51-69 We used the Tukey range test to determine if there is significant statistical correlation between demographic group characteristics. Based on error rates, characteristics were assigned to a group (A or B) to denote if they are statistically different or similar. P values were less than .05 for all tables. We found there was significant difference in error rates between men and women overall. We also determined that older age groups show significantly more errors. The 51-69 age group showed very high error rates as compared to the other groups. We looked at the data broken down by age for each gender. We noticed that the greatest gap of failure rates occurred in the youngest age group (18-24). In this group, women failed significantly more often. We found that differences in height played no distinguishable role in the number of errors. Gender N Mean (Failure Rate) Grouping F 53 8.679 A M 45 5.044 B Age N Mean (Failure Rate) Grouping 51-69 15 12.133 A 36-50 15 8 A B 25-35 35 4.686 B 18-24 34 6.529 B Gender (18-24 year olds) N Mean (Failure Rate) Grouping F 20 9.050 A M 14 2.929 B Results This is an overview of the whole population in our data set based on age and gender. It is clear that age does play a role in error rates. However a larger population could produce different results. It is clear from this chart that there is no significant correlation between height and failure rates. Final Thoughts • Further studies with larger populations are necessary to verify our findings. • A follow up study could be performed to determine if other factors affect these error rates. These factors could include weight, environment, or test administrator. Failure Rate Scatter Plots 35% 39% 26% 61-65 66-71 72-79 69 Subjects with and an average height of 67.8”

(Fall 2012) The Effects of User Characteristics on Iris Capture

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(Fall 2012) The Effects of User Characteristics on Iris Capture