Proceedings of the 20 1 1 IEEEIICME
International Conference on Complex Medical Engineering
May 22 - 25,Harbin,China
Biometric Attendance System
Engr. Imran Anwar Ujan and Dr. Imdad Ali Ismaili
Institute of Information & Communication Technology,
University ofSindh, Jamshoro, Sindh, Pakistan
Abstract - This research work has application for attendance junction. In this research, we will be dealing mainly with ridge
system of employer's and students in general. The system will endings and bifurcations.
facilitate institutions! organization to make attendance individual There are various types of approaches proposed in
in time along with data information thumb impression will be
literature for both image enhancement, and minutiae
taken as a signature for the system entry. Main design and
extraction from fingerprints. The literature on these techniques
challenge in this system is the design of database architecture and
will be examined are reviewed in determining the best
its business logic.
approach to develop for this research. In particular, the
I. AIMS AND OBJECTIVE fingerprint image enhancement algorithm employed by Hong
et al. will be evaluated and implemented to understand how
The aim of this system is to implement in C#.net set of the enhancement algorithm works and how well it performs.
reliable techniques for fingerprint image enhancement and Once a reliable minutiae extraction technique has been
minutiae extraction. The performance of these techniques will implemented and tested, this can be used as the basis of
be evaluated on a fingerprint data set. statistical analysis of fingerprint minutiae.
In combination with these development techniques, statistical The work of Tu and Hartley and Pankanti et al. can be
experiments can then be performed on the fingerprint data set. examined in which a statistical framework for analyzing
The results from these experiments can be used to help us system performance has been presented. Tu and Hartley
better understand what is involved in determining the defined a means of forming a binary code from set of
statistical uniqueness of fingerprint minutiae. fingerprint features and then performing a set of matching
The main aim that this system would test whether experiments on the database to estimate the number of degrees
attendance by fingerprint is enough for identification. It is of freedom within the fingerprint popUlation.
expected that the work in this system will reach the stage of
being able to fully test hypothesis.
II. BACKGROUND/CONTEXT There are some problems which face by fingerprint
recognition or identification security. We can catch a cold by
Fingerprints are the oldest form of biometric identification.
touching a biometric system (fingerprint).
Modem fingerprint based identification is used in forensic
• Twins have identical biometric traits (identical
science, and in biometric systems such as civilian
fingerprints, irises ... ). This is the same clones.
identification devices. Despite the widespread use of
fingerprints, there is little statistical theory on the uniqueness • Stolen body parts can be reused.
of fingerprint minutiae. • Biometric features can be reconstructed from the
A fingerprint is formed from an impression on a surface of template.
composite curve segments. A ridge is defined as a single
• Making a fake finger is easy.
curved segment, and a valley is the region between two
adjacent ridges. The minutiae, which are the local
The inability of fingerprint systems to enroll children and
discontinuities in the ridge flow pattern, provide the details of
small Asian women.
the ridge-valley structures, like ridge endings and bifurcations.
There are 50 to 150 minutiae on a single fingerprint image. III. PROJECT SPECIFICATION
Features such as the type, direction, and location of minutiae
A. Project Description
are taken into account when performing minutiae extraction.
The goal of this project is to daily attendance of employee
The work of F.Galton defined a set of Galton Features for
through fingerprint. The project is design and implements
fingerprint identification, which since then, has been refines
software architecture for fingerprint analysis. The system
and extended to include additional types of fingerprint
should be able to extract key features from a scanned
features. However, most of these features are not used in
fingerprint image and to compare these with a database of
automatic fingerprint identification systems. Instead the set of
known fingerprint images and/or extracted feature sets.
minutiae types are restricted into only two types, ridge endings
For this project we provided with a set of previously
and bifurcations, as other types of minutiae can be expressed
acquired fingerprints and a working fingerprint sensor with
in terms of these two features types. Ridge endings are the
driver software for Windows. Our expectation had fulfilled by
points where the ridge curves terminates, and bifurcations are
most of the algorithm development which executed in C# dot
where a ridge splits from a single path to two paths at a Y-
net and this work done on a Windows PC.
978-1-4244-9324-1/11/$26.00 ©2011 IEEE 499
B. Project Task of project parameters are tentative, the plan will always need
The project can be split into a set of principle tasks to be modified.
representing a progression towards the end goal of a working A structure of BAS software development plan is
fingerprint analysis system. described below
1. We had must reviewed techniques for analyzing
fingerprints and performing pattern recognition on
sets of fingerprints. Several of the most promising Here we describe the brief objectives of the BAS project
and set out the constraints which affect the project
algorithms/ techniques had implemented in C# .net
and initial testing performed on the test set of
fingerprint image provided. • Computerize the daily attendance system
2. The Biometric Attendance System software
• Attendance by fingerprint
architecture for the main system was designed; the
• Protect the proxy which IS doing III daily
main subsystems required were determined and a
method of implementing a full system was evaluated;
work architecture and several of the functional B. Constraints
subsystems were implemented.
3. We analyzed algorithms were implemented and 1. Veridicom Fingerprint Sensor RS.8,500
integrated with the fingerprint sensor, and real-time 2. Expenditure for collection of data and
acquisition and analysis of a fingerprint was information Rs.2500
demonstrated; an improvements in processing speed 3. Total budget is Rs. 1 1 ,000
and implemented and demonstrated.
4. Improvements in the analysis of an acquired image
A rough task breakdown for this project is as follows:
may be achieved through image processing; • Examine and review available literature on image
combining multiple acquired images to provide an
enhancement and minutiae extraction techniques.
enhanced composite image; or more sophisticated
• Develop a series of image enhancement techniques to
statistical or mathematical approaches.
aid the minutiae extraction process.
5. Improvements in pattern matching may be achieved
• Develop a set of reliable techniques to extract the
through various pattern recognition approaches; the
minutiae from fingerprint images.
students should evaluate several approaches,
• Evaluate the performance of the techniques using the
developing an evaluation methodology which enables
fingerprint data set.
a comparison in terms of improved recognition and a
• Use existing techniques as the benchmark for
reduction in terms of false positives and negatives.
comparing the performance of the technique
Integrating the techniques of 4 and 5 with the real-time developed.
acquisition of fingerprints will add significant bonus value. • After reliable minutiae detection techniques have
been developed and tested, then statistical analysis
C. Project Planning experiments on the fingerprint data set can be
Effective management of a software project depends on
performed and documented.
thoroughly planning the progress of the project. We
anticipated problems which arose and prepared solutions to
(Employee Fingerprint Table)
the project problems. A plane, drawn up of a project, we used
as the driver for the project. The initial plane evolves as the [j]EWlD
project progress and better information. O FPRlNT
The planning process starts with an assessment of the
constraints (required delivery date, overall budget, etc)
(Employee Profile Table) (Attendance Table)
affecting the project. This is carried out in conjunction with an
estimation of project parameters such as its structure, size, and
distribution of functions. The progress milestones and
deliverables are then defined. The process then enters a loop.
A schedule for the project is drawn up and the activities
defined in the schedule are initiated or given permission to Fig.1
continue. After some time usually about 2-3 weeks, progress
is reviewed and discrepancies noted. Because initial estimates
orientation and ridge frequency parameters. However, in
practice, this does not pose a significant limitation as
fingerprint matching techniques generally place more
emphasis on the well-defined regions, and will disregard and
image if it is severely corrupted.
Overall, the results have shown that the implemented
enhancement algorithm is a useful step to employ prior to
minutiae extraction. The Crossing Number method was then
implemented to perform extraction of minutiae. Experiments
conducted have shown that this method is able to accurately
detect all valid regions, and will disregard an image if it is
However, there are cases where the extracted minutiae do
not correspond to true minutiae. Hence, an image post
processing stage is implemented to validate the minutiae. The
experimental results from the minutiae validation algorithm
indicate that this additional post processing stage is effective
(a). Flow Chart of Fingerprint
in eliminating various types of false minutiae structures.
In combination with the implemented techniques for image
enhancement and minutiae extraction, preliminary
experiments on the statistics of fingerprints were conducted on
a sample set of fingerprint images. Three types of statistical
data were collected, which include minutiae density, distance
between neighboring minutiae, and ridge wavelength.
Overall, we have implemented a set of reliable techniques
for fingerprint image enhancement, minutiae extraction
Databue Fingerprint fingerprint matching and classification. These techniques we
implemented for employer daily attendance system. Through
which employers attend you by fingerprint only enter their
employer ID and put his finger on sensor.
Our project "Biometric Employer Attendance System
(BEAS)" is an extensible work for any organization or
company in this fast world. Keeping the view of research still
(b). Flow Chart of Fingerprint Matching (Attendan
there is a lot of improvement work and flexibility for the
Fig.2 ERD Model & Flow Charts of Systems coming technologies in the various demanding directions.
The language which we have is very vast and even the under
D. Project Evalution
Microsoft products is trying to rule over the Information
The primary focus of the work in this project is on the
Technology, So we hope that this project will be the point of
enhancement of fingerprint images, and the subsequent
interest for our successors to be enhanced further to market it
extraction of minutiae.
compatible with the demands of the organization
Firstly, we have implemented a series of techniques for
fingerprint image enhancement to facilitate the extraction of
minutiae. Experiments were then conducted using a REFERENCES
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