Biometrics Authentication Using Raspberry Pi

INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY
VOLUME 5 ISSUE 2 – MAY 2015 - ISSN: 2349 - 9303
212
Biometrics Authentication Using Raspberry Pi
L.ARUNKUMAR
PG student
M.E-Embedded System Technologies
Sri Ramakrishna Engineering College
Coimbatore-22
larunkumareee@gmail.com
A.ARUN RAJA
Assistant professor
M.E-Embedded System Technologies
Sri Ramakrishna Engineering College
Coimbatore-22
arunraja21@gmail.com
Abstract— Biometric authentication is one of the most popular and accurate technology. Nowadays, it is used in many real time
applications. However, recognizing fingerprints in Linux based embedded computers (raspberry pi) is still a very complex problem.
This entire work is done on the Linux based embedded computer called raspberry pi , in which database creation and management
using postgresql, web page creation using PHP language, fingerprint reader access, authentication and recognition using python were
entirely done on raspberry pi This paper discusses on the standardized authentication model which is capable of extracting the
fingerprints of individual and store that in database . Then I use the final fingerprint to match with others in fingerprints present in the
database (postgresql) to show the capability of this model.
Index Terms— fingerprint authentication, PHP, postgresql, python, raspberry pi.
1 INTRODUCTION
The human body has the privilege of having features
that are unique and exclusive to each individual. This exclusivity
and unique characteristic has led to the field of biometrics and its
application in ensuring security in various fields with various
embedded controllers and embedded computers. Biometrics have
gained popularity and has proved itself to be a reliable mode of
ensuring privacy, maintaining security and identifying
individuals. It has wide acceptance throughout the globe and now
is being used at places like airports, hospitals, schools, colleges,
corporate offices etc.
Biometrics is the study of identifying a person by their
physical traits that are inherent and unique to only the person
concerned. Biometric identification include fingerprint
verification, palm geometry, face recognition, iris recognition,
etc. The above mentioned techniques work with different levels
of functionality and accuracy.
Accuracy and reliability are the two most important
parameters when it comes to biometric applications and that too
with advanced embedded computers. Fingerprint verification is
one of the oldest known biometric techniques known but still is
the most widely used because of its simplicity and good levels of
accuracy. It’s a well known fact that every human being is born
with a different pattern on the fingers and this feature is exploited
to identify and differentiate between two different persons that is
what the factor which helped to initiate the model .
2 RELATED WORKS
2.1 DEVICE SUPPORT
Through prior involvement with fingerprint scanning
efforts on Linux, I tested different devices to support with
raspberry pi. I identified the key characteristics of each device
and checked for the compatibility of each device. Finally
concluded with U.are.U 4500 Module which suits the application
I tried for chapter 3 covers the technical information’s of the
fingerprint device used in this proposed design.
2.2 LITERATURE SURVEY
Sonam Shukla, Pradeep Mishra suggested increasing
the Accuracy of an Existing Fingerprint Recognition System
Using Adaptive Technique, in this approach developer mainely
focusing onIntegrated Automated Fingerprint Identification
Service (IAFIS) of the most famous police agencies.[1] They
extracted fingerprint pattern is characterized by a set of
ridgelines that often flow in parallel, but intersect and terminate
at some points. The uniqueness of a fingerprint is determined by
the local ridge characteristics and their relationships. Main
drawback of this model is this approach is not so apt for real time
applications but the accuracy of system is highly adaptable. Most
automatic systems for fingerprint comparison are based on
minutiae matching.
Le Hoang Thai and Ha Nhat Tam in 2010 suggested
Fingerprint recognition using standardized fingerprint model,
now a days, fingerprint recognition is one of the most Important
biometric technologies based on fingerprint distinctiveness,[2] in
this approach they focused on improving the quality of
fingerprint images. In fingerprint recognition process, the
important step which affects on system accuracy is matching
between template and query fingerprint. Many solutions are
designed to increase this step’s accuracy these matching
algorithms may be classified into three types: minutiae-based
approach, correlation-based approach and feature-based
approach. However, as analyzed, the score of these algorithms is
not high (especially in case fingerprints are of the same finger
but they are rotated or the intersection is too small). So, it’s
Necessary to design a model to standardized fingerprint template
in order to improve matching score.
Mukesh Kumar Thakur, Ravi Shankar Kumar, Mohit
Kumar, Raju Kumar suggested Wireless Fingerprint Based

213
Security System Using Zigbee Technology [3]. This approach
functions based on the uniqueness of each person and it
integrating the biometric device along with zigbee to transmit the
information obtained in this approach they are using fingerprint
extraction and matching algorithm and they maintaining the
database to authenticate the person who approaching for the
access through the online web page created in the local server.
3 SYSTEM OUTLINE
3.1 HARDWARE ARCHITECTURE
This proposed system consists of raspberry pi and
fingerprint module. This system provides the features of real time
authentication facilities
Fig 1: proposed system Block diagram
3.1.1 RASPBERRY PI
Hardware is a physical device that can be touched or held,
like a hard drive or a mobile phone. Software can be thought of
as a program or a collection of programs that instruct a computer
on what to do and how to do it. Below is an image of the
Raspberry Pi which describes some of the components that make
up the hardware.
Fig.2. Hardware Components of Raspberry Pi
Fig.2 shows the hardware description of raspberry pi.
The real time vehicle tracking system uses the GPIO pin, Micro
SD slot, USB port and Micro USB connector. The GPIO pins are
used for serial communication for interfacing GSM and GPS. It
uses 8GB SD for installing the Raspbian OS and for storage. The
USB port is used for connecting keyboard, mouse, dongle and
pen drive. The power supply is given through USB connector.
3.1.2 U.are.U 4500 USB FINGERPRINT READER
The U.are.U 4500 is the module which I used in this
project where this Module is a miniature USB fingerprint reader
designed for integration in to OEM equipment where fingerprint
verification or identification is needed. This module supports
both windows and Linux based operating system. This self-
contained module optically scans the fingerprint when the user
touches the glowing window.
Fig 3: fingerprint module
Optical technology gives the highest quality fingerprint
templates and reliability along with the raspberry pi embedded
computer. The U.are.U 4500 Module is designed to simplify
OEM integration. The module is sealed from dust and includes
convenient mounting features.
The device can automatically control calibration,
encryption, and data transfer through the USB interface. A
―Heavy Duty‖ version of the module is available for unattended
public installations and other high-use applications. While
checking the compatibility of this module I have found this
module to be more reliable for all kind of OS, even its easy to
interface with raspberry pi (debian os) .The U.are.U 4500
Module and digital Persona Fingerprint Recognition Engine have
an unmatched ability to authenticate even the most difficult
fingerprints accurately and rapidly.
3.2 SOFTWARE ARCHITECTURE
For this project I have used softwares like PHP,
postgresql, opencv (python script). The configuring procedures,
saving and retrieval of fingerprint templates procedures are
mentioned in the upcoming chapters.
3.2.1 PHP
PHP is a server-side scripting language designed
for web development but also used as a general-purpose
programming language which is been used in the project. As of
January 2013, PHP was installed on more than 240
million websites (39% of those sampled) and 2.1 million web
servers. Originally created by Rasmus Lerdorf in
1994, the reference implementation of PHP (powered by

214
the Zend Engine) is now produced by The PHP Group.[6]
While
PHP originally stood for Personal Home Page, it now stands
for PHP: Hypertext Preprocessor. This is been used to display the
information’s of workers in the monitor.
3.2.2 POSTGRESQL
PostgreSQL, often simply "Postgres", is a object-
relational database management system which is used along
with an emphasis on extensibility and standards-compliance. As
a database server, its primary function is to store data securely in
the raspberry pi, supporting best practices, and to allow for
retrieval at the request of other software applications like PHP. It
can handle workloads ranging from small machine applications
to large Internet facing applications with many concurrent users
even through the terminal in the raspberry pi server. Recent
versions also provide replication of the database itself for
availability and scalability in both windows and linux.
3.2.3 SOFTWARE- ALGORITHM
The software algorithm of authentication system is
described here, the IP address in putty is initialized.
Tightvncserver is used for viewing raspberry pi.
Step 1 : Initialize IP address in PuTTY.
Step 2 : Run the tightvncserver.
Step 3 : Connect the fingerprint module.
Step 4 : open the fprint_demo gui
Step 5 : read and save the image template
Step 6 : covert the image template in to binary template
Step 7 : save the obtained template in the postgresql
database
Step 8 : now comparison between various templates can
be carried out using the python script
Step 9 : The accurate matching points will obtain
between the images
3.3 IMPLEMENTATION PROCEDURE
3.3.1 FPRINT DEMO: GRAPHICAL
DEMONSTRATION APPLICATION
This proposed system is implemented in a Linux based
GUI application, fprint demo and fingerprint model, with the
intention of using this to demonstrate the functionality of the
finger print device along with raspberry pi embedded computer.
fprint demo offers an interface for enrolling fingers and deleting
enrollment data for previously enrolled fingers with the help of
fprint GUI, an interface for verifying a specific finger and an
Interface for identifying a finger from a selection of previously
enrolled fingerprint data. For imaging devices, it shows the
scanned fingerprints on-screen and allows you to view the
binarized version with minutiae plotted in the GUI.
Fig 4:capturing of fingerprint template
3.3.2 CONVERTING THE TEMPLATE IN TO
BINARAIZED TEMPLATE
This GUI is capable of converting the fingerprint
template in to binary template. The imaging performance of this
device is excellent. The returned images are large and finds a
large number of minutiae, leading to suitably distinct scores for
matching/non-matching fingers. Fig 5 shows an image returned
by this driver and its binarized form with minutiae plotted with
the help of raspberry pi embedded computer.
Fig 5: normal and binarized template
4 EXPREIMENTAL RESULTS
After extracting the fingerprint template using fprint
demo GUI, I was able to store the binarized image in the data
base using the PHP script
Then comparison has been carried out with the help of
open cv programming tool with python script
The below figure shows the image of mismatched
fingers, which is identified by the python script which uses the
special image processing algorithm called
FLANN_INDEX_KDTREE with cv2.FlannBasedMatcher
Fig 6 given below shows mismatched fingerprints of
different persons the python program is running as the
background process

215
Fig 6: mismatched finger ridges in template
Thus the above figure shows the mismatched
characteristics of two different fingers, while comparing the
same fingers I got the matching points almost every where in
finger templates
Fig 8 given below shows exactly matched fingerprints
of a person the python program is running as the background
process
The green coloured lines connecting two templates
showing the number of matching points in the templates
Fig 7: matched finger ridges in template
The above experimental results clearly states the ability
of the proposed design to distinguish the matched and
mismatched fingers.
5 CONCLUSIONS AND FUTURE WORK
Fingerprint recognition is one of the most popular and
accurate Biometric technologies. Nowadays, it is used in many
real time applications. However, recognizing fingerprints in
Linux based embedded computers (raspberry pi) are still a very
complex problem. This entire work is done on the Linux based
embedded computer called raspberry pi , in which database
creation and management using postgresql, web page creation
using PHP language, fingerprint reader access, authentication
and recognition using python were entirely done on raspberry pi
This paper discusses on the standardized fingerprint model which
is used to synthesize the template of fingerprints. In this model,
after pre-processing step, find the transformation between
templates, adjust parameters and synthesize fingerprint. Then i
use the final fingerprint to match with others in fingerprints
present in the database (postgresql) to show the capability of this
model.
Fine tuning has to be done to improve the accuracy of
the system and developing the system for real time higher end
application are need to be done as the future work for this design.
REFERENCES
[1] Sonam Shukla, Pradeep Mishra [2012],
"Increasing The Accuracy Of An Existing
Recognition System Using Adaptive
Technique" International Journal of Advanced
Research in Computer Science and Software
Engineering, Volume 2, Issue 6, PP 52-57.
[2] Le Hoang Thai and Ha Nhat Tam [2010],"
Fingerprint recognition using
Standardized fingerprint model" IJCSI
International Journal of Computer Science
Issues, Vol. 7, Issue 3, PP 11-16.
[3] Mukesh Kumar Thakur, Ravi Shankar
Kumar, Mohit Kumar, Raju Kumar
[2013],"Wireless Fingerprint Based Security
System Using Zigbee Technology"
International Journal of Inventive

216
Engineering and Sciences (IJIES),ISSN:
2319–9598, Volume-1, Issue-5, PP 14-17.
[4] Arun, Emmanuel., Diwakar& Rajeswari
―Automated attendance system using
biometrics with Embedded web server‖
Graduate Research in Engineering and
Technology (GRET): An International
Journal, page No-(54 to 57)
[5] Karthik Vignesh E, Shanmuganathan S,
A.Sumithra S.Kishore and P. Karthikeyan ―A
Foolproof Biometric Attendance Management
System‖ International Journal of Information and
Computation Technology. ISSN 0974-2239
Volume 3, Number 5 (2013), pp. 433-438
[6] www.postgresql.org
[7] www.tutorialspoint.com
[8] www.raspberry pi.org

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