ENGR 103 - Spring 2013
Freshman Engineering Design Lab
Freshman Engineering Design Lab
Biometric
Recognition for Control
Project Design
Proposal
Date
Submitted: April 9, 2013
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Submitted
to:
|
Chris
Lester, clester@minerva.ece.drexel.edu
|
Group
Members:
|
Dipesh
Bhakta, dhb39@drexel.edu
|
Sachin
Gandhi, sag@drexel.edu
|
|
Berk
Ozoglu, bo73@drexel.edu
|
|
Aravind
Ponukumati, asp79@drexel.edu
|
|
Abstract:
The motivation of this project is to
create a system that would enhance the security and privacy for multiple users
on their personal computers. The goal is to create an application that would
utilize multiple biometric characteristics, such as facial features, voice, and
fingerprints, to correctly identify an user and allow him/her to access his/her
material on a computer. The technical challenges the group expects to face in
the process of this project are creating a signal processing system that will
make use of a webcam to identify facial features, a microphone to identify
vocal patterns, and a fingerprint scanner to identify fingerprints. Another
challenge is interfacing the signal processing systems together to function in
identifying a person correctly. The final deliverable will be a MATLAB script
that will be able to integrate a standard webcam, microphone, and fingerprint
scanner to correctly identify a user and grant him/her access to his/her
account on a computer.
Introduction
Biometric recognition is a rapidly-developing pattern
recognition system used for a variety of purposes including verification,
identification, and security as seen in Figure 1 [1]. Biometric recognition has
applicability for individuals with restricted mobility such as those who cannot
type or speak their password and acts as an additional safeguard for security
purposes. Many biometric recognition systems “conduct a one-to-many comparison
to establish an individual’s identity” [1]. It is also much more difficult for
hackers and those with malicious intentions to forge or replicate biometric
features. Many unique individual features can be used to distinguish one person
from another such as fingerprints, facial features, irises, hand geometry, and
even a person’s voice [1].
Biometric recognition is a rapidly-developing pattern
recognition system used for a variety of purposes including verification,
identification, and security as seen in Figure 1 [1]. Biometric recognition has
applicability for individuals with restricted mobility such as those who cannot
type or speak their password and acts as an additional safeguard for security
purposes. Many biometric recognition systems “conduct a one-to-many comparison
to establish an individual’s identity” [1]. It is also much more difficult for
hackers and those with malicious intentions to forge or replicate biometric
features. Many unique individual features can be used to distinguish one person
from another such as fingerprints, facial features, irises, hand geometry, and
even a person’s voice [1].
Figure 1. Sample biometric recognition
flowchart for verification and identification of an individual.
The major tasks to be performed throughout the ten-week
project are to develop a multi-faceted identification system that can
cross-reference a person’s facial photograph and fingerprint with an existing
database. There are inherent challenges when trying to accomplish this task,
primarily due to the complexity of biometric features and the generation of a
unique template for each individual. In the end, the desired result is to
successfully identify, with minimum errors in identifying the wrong individual
or failing to identify the proper individual, a person using multiple
physiological characteristics.
Deliverables
At the conclusion of the project, a successfully working software model will be
developed that is capable of identifying an individual using multiple biometric
identifiers such as facial features and fingerprinting. To achieve this goal,
an external fingerprint scanner will be purchased and the software will be
developed to take webcam input into MATLAB software. The intended design will
contain a database of various biometric templates for predetermined individuals,
and simulations will be conducted to attempt to identify various individuals in
the lab group and volunteers. All of these test cases will also be presented at
the end of the project to assess the functionality of the design.
Schematics will be developed early in
the term to plan out the design and setup of the project. Flowcharts and
pseudocode will also be prepared to direct the progress of writing the code.
Old developments of the code will be saved after completion of major milestones
such as implementation of fingerprint analysis and digitization of various
physiological features captured by the webcam.
Technical Activities
Literature Study and Signal Processing Introduction
This task will mainly include initial research and getting acquainted with the process in general. It will include planning how the other tasks will be completed as well as research that needs to be done in order to find a solution to the problem.
Digitization of Facial Features
This task will consist of setting up one of the main forms of signal processing in which the viewers face will be recognized. It will involve the use of a webcam built into many personal computers. In order to achieve this goal, code will be used to identify facial features based on an algorithm integrated into the program.
Voice Identification
Voice identification will be another method of recognizing individuals and add another layer of security in the identification process. This task will include design of a systematic algorithm that can identify a person by analyzing their speech patterns and tone.
Fingerprint Analysis
Fingerprint analysis will include setting up the fingerprint
sensor and integrating it into MATLAB. The analysis will then make use of code
to analyze the outputs of the sensor and a response from the system.
System Integration
This task will focus on the system as a whole as it forms and
individual pieces will be incorporated. The design will be assembled and
physical issues will be addressed.
Testing and Debugging
Testing will take place using the group members as well as
other individuals that would like to participate. Correct identification of
faces in the database will be the main concern, while other minor bugs such as
issues with the output of the system will be addressed.
Final Report Preparation
This spot is reserved for preparing anything to do with the
final report and presentation, from planning the presentation to editing the
report.
Project Timeline
The timeline for completion of the project is given in Table 1 below. Time for
literature review and familiarization with biometric recognition has been
allotted. In addition, some knowledge of image and signal processing is
required for facial and voice recognition, respectively.
Table 1. Biometric recognition
timeline over a 10-week period. Various weeks have been allotted for literature
study, development of voice, fingerprinting, and facial feature identification
as well as testing.
By around Week 2, it is expected that some sort of algorithm
is being developed for the voice and facial feature identification. The
fingerprinting analysis is added later to the project because it may take time
for the hardware to arrive. However, it is expected that the system is being
integrated by around Week 5 and testing and debugging occurs by Week 6. It is
at this point that official test cases can be analyzed to ensure that the
biometric recognition is working as expected. The final report is then
developed by Week 8 through to the end of the term, and the testing should be
completed by Week 9 at the latest.
Facilities and Resources
The group intends to make use of a computer webcam to obtain
sample photographs of subjects being identified. This resource will be used to
identify various facial features in the subject like distance between eyes,
skin tone, and various other distinguishing characteristics [2]. Another
resource that will need to be purchased is an external fingerprint scanner.
Unlike fingerprint scanners that may be built-in to computers, the external
fingerprint scanner can be attached to any computer with appropriate drivers
and be yet another method of identification for biometric sensing [2].
Fingerprint recognition techniques are already prevalent in the market and
therefore an obvious choice for preliminary biometric identification of an
individual.
Expertise
Developing a functional computer application capable of doing intensive image
and signal processing requires significant prior experience with computer
programming. Familiarity with MATLAB/Java is recommended for this project
because of the well-written API and preexisting classes for processing external
video and audio output. In addition, some knowledge of biomedical engineering
is useful to understand which physiological features are unique amongst
individuals. For example, it is important to know that features like
fingerprints can be practically used to identify people while other features
like the shape of the head may be too general for implementation. Some existing
biometric technologies and their advantages and disadvantages are seen in
Figure 2:
Figure 2. Pro-con analysis table of
biometric technologies identifying various physiological features.
Some knowledge of the technology being used such as the
webcam and fingerprint scanner would also be a boon while completing the
project. Being able to interface the external hardware to MATLAB is a critical
component of the project to be able to gather the input data. In addition, some
knowledge of signal processing techniques should be learned during the
literature study period to become more advanced in the subject.
Budget
The breakdown of the project budget is given in Table 2. Various hardware
materials have been accounted for and materials that can be obtained free of
charge has not been tabulated.
Table 2. Budget summary detailing
hardware costs for biometric sensors.
Fingerprint Reader
The Eikon fingerprint reader has a capacitive sensor and is
already built with the functionality to perform “biometric sensing in the
device” [3]. The component will be used as a preliminary method of
identification and an eventual check as to the identity of a person trying to
access the computer in question.
7.2 Webcam
The Logitech Webcam has a sensor that takes in light. The
webcam then converts this light into electrical signals, which are fed to a
processor and then finally converted into a digital image. This component
serves to assess the facial characteristics of an individual. This information
will be fed into a script that determines the identity of a person.
7.3 Microphone
The built-in microphone in Apple head will receive audio input. This component
will function alongside a MATLAB code to identity the vocal patterns of a user, and
compare them with the ones stored in the database of user information.
References
[1] A. K. Jain. (2007). “Biometric
recognition.” Nature. [Online]. 449, pp. 38-40.
[2]
S. Prabhakar. (2003, March). “Biometric recognition: Security and Privacy
Concerns.” IEEE Security and Privacy. [Online]. 1(2), pp. 33-42.
[3]
Anonymous. “UPEK Eikon swipe fingerprint
reader.” Internet. [2013, April 7].
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