1. THE EVOLUTION AND ADVANCEMENT OF A GRADUATE COURSE IN BIOMETRICS
Stephen J. Elliott 1 and Eric P. Kukula 2
Abstract  During the Fall of 2002 a biometrics course engage in research projects in the laboratory is also
was developed to encourage cross-disciplinary education hampered by their mathematical backgrounds. At the
and research, which addressed two core areas: biometric same time however, we must not forget the core mission
technologies and their applications. The goal of the of the College of Technology which directs faculty to
course initially was to provide students with a functional balance the competing demands of research and
knowledge in biometrics that they could transfer to a education.
career in the information security and technology
industry. However, since the initial offering in 2002, the PREVIOUS COURSE OFFERINGS
course has been modified to accommodate students with
The original course development and syllabus
diverse backgrounds and interests. This paper discusses
for Biometric Technology and Applications is outlined in
the evolution and advancements the course has
detail in [2]. The course was taught from the viewpoint of
undertaken since the initial offering and the framework
systems integrator, purchaser and evaluator. In addition,
for future modifications to increase the skill sets of the
the course examined the advantages and disadvantages of
intended audience.
the individual biometric technologies, the fundamentals of
testing and evaluation, writing technical reports and
Index Terms  curriculum development, biometrics,
graduate education presentations, and understanding the process of biometric
standards. The first course was offered in the Fall of 2002.
INTRODUCTION Twenty students participated in the course, with a
majority of students being junior or senior undergraduate
Biometrics is defined as the automated students in Computer Information Systems Technology or
recognition of individuals based on their behavioral and Industrial Technology. The course was introductory in
biological characteristics [1]. Traditionally biometrics has nature, covering the general aspects of biometric testing
been limited to academic disciplines such as Computer and evaluation. At the same time, the lab was fairly small
Science, Electrical Engineering, and Statistics. For with limited equipment which necessitated the overview
example, algorithm development typically occurred style of the course.
within computer science, while speech and computer The second semester the course was offered saw
vision developed in electrical engineering. As biometric an increase in the number of non-undergraduate
technology evolves and matures, additional disciplines Technology majors. Twenty seven students took part in
have gained an interest in biometrics including; the class, with seven from Aviation Technology,
Technology, Ergonomics, Management, and Political Computer Science, and Information Security.
Science. The realization of converging disciplines in Furthermore the course was added as a School of
biometric technology was accepted by the authors and Management elective. To accommodate the
resulted in the creation of a multi-disciplinary class in interdisciplinary audience discussions in management,
Biometric Technology and Applications in the Fall algorithm development, and integration were added to the
semester of 2002, with the aim at encouraging cross- course. Furthermore, the lab moved to larger facilities that
disciplinary education and research. The course benefited included 11 workstations and enabled the course to have a
from the integration of research and engagement through more substantial laboratory experience and also enabled
the deployment of biometrics equipment into an students to work on more complicated research projects.
educational environment. However, as the technology has During the 2003-2004 academic year the
advanced, the curricula, specifically the mathematical instructors of the course developed a laboratory manual so
prerequisites, of the students taking the course have not. that students could complete a more independent style of
Therefore a dichotomy exists where enrolled students are research while interacting with the biometrics technology.
not prepared mathematically or statistically for the Enrollment remained at about 20-25 students per
projects that the newer technology would allow them to semester. The course started to incorporate more applied
pursue. Their ability to develop an interest and fully research than previously – typically testing and evaluation
1 Stephen Elliott, Ph.D., Assistant Professor, Biometrics Standards Performance, and Assurance Laboratory, Department of Industrial Technology, Purdue
University, 401 North Grant Street, West Lafayette, IN 47906, USA, elliott@purdue.edu
2 Eric Kukula, Research Assistant, Biometrics Standards Performance, and Assurance Laboratory, Department of Industrial Technology, Purdue University,
401 North Grant Street, West Lafayette, IN 47906, USA, kukula@purdue.edu
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World Congress on Computer Science, Engineering and Technology Education
89

2. of commercially available products, thus giving students successfully interact with the laboratory and research
contact with companies in the biometrics industry. projects.
However the needs required by the research indicated that The course was designed as an introductory
the course would have to become more statistically course in biometric technology and applications. As such,
orientated. it has had the mission of teaching College of Technology
During the 2004-05 school year a course students an overview of the individual biometric
textbook was developed specifically for the purpose of modalities and usually consists of a semester project that
this class as there was no appropriate text available for the provides students with the knowledge to implement
biometrics practitioner. In addition to the text, the class biometric technologies into their workplace [1]. With the
moved into e-learning, as all readings, assignments, and increase in statistical analysis, a balance had to be struck
directions were maintained in WebCT Vista™. Semester to cater to the students in the course through a challenging
projects were more varied, ranging from investigating course structure, yet at the same time maintain interest so
new hand geometry techniques, to securing a that they can understand the material, and gain a benefit
manufacturing environment with biometric technologies, for the course. This was done through case studies and
and netorking biometric devices. The lab continued to practical experiences. Discussions with the students
grow, and moved again into its current location, as shown highlighted a “fear” of statistics, mainly because the only
in Figure 1. Over $700,000 worth of equipment had been statistics courses they had participated in were either back
purchased or donated resulting in students having access in high school, or early on in their collegiate career.
to many different biometric modalities. The number of Further examination of typical students’ plans of study
students remained constant from previous semesters but revealed a deficiency in higher mathematics courses at the
as the class continued to move towards data collection collegiate level. For example, the Industrial Technology
and analysis, it was clear that the course needed to be curriculum includes a freshman (100) level algebra and
adapted to provide more information on statistics. In trigonometry course, and a junior (300) level course in
addition to the lectures, students used the equipment statistical quality. The plan of study in Computer and
purchased and donated to the Biometrics Standards, Information Technology has students taking two 200 level
Performance, and Assurance (BSPA) Laboratory in the Mathematics courses which deal with calculus. There was
Department of Industrial Technology. one statistics course in the Computer Information
Technology plan of study. Although useful, none of these
courses relate to the mathematics and statistics covered in
the biometrics field. So the challenge therefore is to
present the technology in an easy to understand format,
and also teach some of the most important mathematical
concepts.
ADAPTATION OF OTHER COURSES
A review of various biometric literature was
undertaken – books that were basically introductory in
nature [2-20], to examine what types of statistics and
mathematics were being used, and whether any of the
major topics were being excluded from the previous
editions of the course because of their mathematical
nature. It must be noted that students at the undergraduate
FIGURE. 1 level in the two major areas of Industrial Technology and
BSPA LABORATORY IN THE DEPARTMENT OF INDUSTRIAL
TECHNOLOGY. Computer Information Technology would not have had
any previous experience with statistical software such as
SAS™, Minitab™, and SPSS™. Furthermore, they would
REASONS FOR COURSE CHANGES have no prior experience with MATLAB™ either.
Identifying the missing gaps of knowledge is one thing,
The course has benefited from the integration of but students in the College of Technology tend to learn
research and engagement through the deployment of the best if they can interact with data in a hands-on
equipment into an educational environment. However as environment. The easiest solution was to have the
was mentioned earlier, a dichotomy has developed students create data themselves (keystroke dynamics was
between the preparation of the students via their chosen due the very small feature set), and analyze the
prerequisites, and the knowledge they need to more data from there – introducing statistical and mathematical
concepts through experimentation as opposed to lectures.
©2006 WCCSETE March 19 - 22, 2006, São Paulo, BRAZIL
World Congress on Computer Science, Engineering and Technology Education
90

3. So the course was adapted from its previous CURRENT COURSE OFFERING
version as described in [1], to include mathematical and
statistical concepts. The first exercise was to initially The Fall 2005 course was updated and
collect data so that students could examine the redesigned to provide students with the ability to make
repeatability of samples, and undertake some elementary “biometrics happen” in their place of work. Topics for the
statistical calculations. With this assignment they learn course included:
about concepts such as outliers, the Gaussian distribution, • Discussing biometrics and their broader role in
kurtosis, skewness, and the basics of data collection and Automatic Identification and Data Capture (AIDC)
data integrity. From these basic steps, probability emerges technologies.
and must be understood by students, as biometrics do not • Detailed exposure and lab activities on each biometric
return binary scores. This leads into a discussion on modality.
hypotheses development – whether an individual is going • Design experiments, enabling students to design
to be accepted into the system, or whether there are any testing and evaluation protocols that can be used
statistically significant differences in image quality – two during the course or in the graduate research.
examples that the instructors use to convey probabilistic • Introduction of mathematical and statistical concepts,
and mathematical concepts to the students. It is envisaged outlining for the technologist basic elements of
that the next run of the course will include some pre- and concepts used in biometrics.
post testing of the students knowledge now that the first • Introduction to the standards development process and
semester run through and development has been biometric standards initiatives.
completed. The course continues with a discussion on • Privacy Issues
power and significance, and this leads nicely into the • Vulnerabilities and attacks to biometric systems.
development of a threshold value, False Match Rates, and • Implementation project which gives students practical
False Non-Match Rates. Students can relate this experience designing, building, implementing a
information back to the initial keystroke data collection. biometric system in an operational environment.
Another adjustment to the course has been to The design of this particular offering was a
introduce more applied research activities. The lab often balance between practical and theoretical. To balance the
undertakes testing and evaluation for commercial entities theoretical out, industry representatives were brought in to
and this provides opportunities for students to interact discuss individual biometric modalities, as well as their
with real world problems and data. This semester, there applications and real-world implementations. Table 1
are three major projects – the first two projects are below outlines the similarities and differences between
continuations of course projects from previous semesters the initial offering in 2002 and the current offering in
and involve Hand Geometry in the Recreation Center 2005.
[21], and the implementation of Biometrics in a
Manufacturing Environment [22]. The third research TABLE I
project examines how hand readers perform at an elderly COMPARISON OF COURSE SYLLABI FOR COURSES TAUGHT IN 2002 AND
residential home. In this project, students in the class have 2005
to go out to the residential home and collect hand data. Week 2002 2005
They will then analyze the scores, and provide statistical Introduction to
evidence on how the hand reader performs with an elderly 1 Introduction to Biometrics Biometrics
population vis-à-vis an 18-25 population. All of these Biometrics and the Role
Human Subjects in AIDC
projects provide the students with valuable learning
Biometric Technology Dynamic Signature
opportunities that require them to collect data, provide 2 Overview Verification
feedback on the data collection, statistically examine the Biometrics and Aviation
data, and write up a technical report. (Case Study) Definitions
This change to the course has resulted in the first Taxonomy and Testing Mathematical Concepts
3 Procedures and Statistics
seven weeks being devoted to mathematical and statistical
Legislation, Standards,
properties. The next part of the course examine the Testing and Regulatory Mathematical Concepts
individual biometric modalities. These too were discussed 4 Bodies and Statistics
in [1], although there have been some additions to the Mathematical Concepts
course. Given that the students have had seven weeks of 5 Electronic Signatures and Statistics
Forgery Experiments
mathematics and statistics, they can now analyze data
Electronic Signature
using software tools that was previously explained to 6 Analysis Human Subjects Testing
them in a class lecture. It is hoped that this will increase 7 Hand Geometry Fingerprint Recognition
their understanding of the various topics. 8 Fingerprint Recognition Fingerprint Recognition
Fingerprint Image
Biometric Security Issues Quality
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World Congress on Computer Science, Engineering and Technology Education
91

4. 9 Face Recognition Iris Recognition 8. Elliott, S., Biometric Technology: A primer for Aviation
Face Recognition at Purdue Technology Students. International Journal Of Applied Aviation
University Airport (Case Studies, 2002. 3(2): p. 311-322.
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Creating and table-based digitizers. ETRI Journal, 2004. 26(6): p. 641-646.
10 Iris Recognition Maintaining Databases 10. Fairhurst, M.C., Signature verification revisited: promoting
Human Factors and practical exploitation of biometric technology. Electronics &
Biometric Device Communication Engineering Journal, 1997: p. 273-280.
11 Voice Recognition Performance 11. Howell, A., Introduction to Face Recognition, in Intelligent
Face Recognition (2D Biometric Techniques in Fingerprint and Face Recognition, L.
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Biometric Implementations 12. Jain, A., R. Bolle, and S. Pankanti, Introduction to Biometrics, in
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Biometric Standards
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14. Moore, G. and D. vonMinden, The History of Fingerprints,
FURTHER WORK onin.com, Editor. 2003.
15. Newton, H. and J. Woodward, Biometrics: A Technical Primer.
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16. Pankanti, S., R.M. Bolle, and A. Jain, Biometrics: The Future of
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evaluation methods, a summative evaluation will also be Elderly Population vis-à-vis 18-25 Year Olds, in Industrial
designed to measure the overall effectiveness of the Technology. 2003, Purdue University: West Lafayette, IN.
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hand geometry at Purdue University’s Recreational Center. An
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