50409621003- fingerprint recognition system-ppt
DESCRIPTION
Fingerprint Recognition System-PPTTRANSCRIPT
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FINGER PRINTSRECOGNITION SYSTEM
S.ANITHALAKSHMI
50409621003
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Abstract
The minutiae are ridge endings or bifurcations on thefingerprints. They, including their coordinates and
direction, are most distinctive features to represent the
fingerprint.
Most fingerprint recognition systems store only the
minutiae template in the database for further usage.
The conventional methods to utilize minutiae
information are treating it as a point set and finding the
matched points from different minutiae sets.
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This kind of minutiae-based fingerprint recognition
systems consists of two steps, i.e., minutiae
extraction and minutiae matching.
In the minutiae matching process, the minutiae
feature of a given fingerprint is compared with theminutiae template, and the matched minutiae will be
found out.
The template used for fingerprint recognition isfurther utilized in the matching stage to enhance thesystem’s performance.
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These templates are been stored in the database for further
processing.
Specific unique id is generated for each template stored.
The id is stored in the database along with the template locations.
Next is the verification process where you need to provide the id
for comparison.
The given id is being compared with the id’s in the database and
matched with the corresponding template of that id.
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A message is being displayed on successful matching along
with the score.
Otherwise an failure message is displayed indicating match not
found.
In the identification stage we need not specify an id. Click on
the Identify button which searches for any match and provides
the corresponding result.
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The database records can also be deleted through the
application.
Auto extract and Auto identify check boxes can be selected if
need which automatically extracts and identifies the matching
image
It is also possible to load an image and compare it with the
database images.
The colors of the template extraction can also be changed.
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ORGANIZATIONAL PROFILE
ORATOR SOLUTIONS
The name “Orator”– A Good Speaker, One who speaks
well in public. A good speaker has lot of followers.
Like that, We people are good speaker by our work. Wesatisfy our clients by our services. And we are here to
provide Intelligent
SKILLS
Banking & Real Estate
Finance & Insurance
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o Hospital and health care industry
o Web Applications
o Office Automation
o Manufacturing Retailing
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HARDWARE REQUIREMENTS
Processor PENTIUM IV
RAM 128 MB
Hard Disk 40 GB
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SOFTWARE REQUIREMENTS
Browser Internet Explorer
Server side scripting Java
Database Ms-Access
Client side scripting HTML
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Existing System
The conventional methods to utilize minutiae
information are treating it as a point set and finding the
matched points from different minutiae sets.
In existing system, the Sparse areas are not considered.
So the result may not obtain correctly. And the
matching will be difficult to get an absolute result.
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FingerPrint ViewRed SpotsMinutiae
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Proposed System
In Proposed system, we considered the sparse area
and the fingerprint’s orientation field is reconstructedfrom minutiae and further utilized in the matching
stage to enhance the system’s performance.
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DESIGN OF THE PROJECT
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Data Flow Diagram
Show the matching Score
Thump Impression
Extract
Particular Identify
Entire Verification
Database
If Matches Show the Particular ID No
Does Not Exist
False
True
If Matches
Does not match
False
True
Enroll
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Module List
Minutiae Template
Minutiae Matching
Effective Region Estimation
Orientation Field Matching
Fusing Matching
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Minutiae Template
Minutiae templates are a fraction of the size of
fingerprint images, require less storage memory
and can be transmitted electronically faster than
images.
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Minutiae Matching
In this module we matches the fingerprint minutiae by using both the local and global structures of minutiae.
The local structure of a minutia describes a rotationand translation invariant feature of the minutia in itsneighborhood.
It is used to find the correspondence of two minutiaesets and increase the reliability of the global matching.
The global structure of minutiae reliably determinesthe uniqueness of fingerprint. Therefore, the local andglobal structures of minutiae together provide a solid
basis for reliable and robust minutiae matching.
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(a) X Person’s Fingerprint (b) X Person’s Fingerprint for
verification
Matching Stage
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Effective Region ESTIMATION
we can extract the effective region by finding the
smallest envelope that contains all the minutiae
points. For an When only having minutiae feature, wecan extract the effective region by only using
minutiae illustration. Here, we put the original image
together for the convenience to give a visual sense.
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Estimation of Effective Region
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Orientation Field Matching
To compare two fingerprints’ orientation field, thefirst step is alignment of these two fingerprints. Thealignment is mainly based on minutiae information .Here we choose the Hough transform based approach
to finish the alignment due to its simplicity.
Hough Transform (HT) is one of the most commonmethods for detecting shapes (lines, circles, etc.) in
binary or edge images. Its advantage is its ability todetect discontinuous patterns in noisy images, but itrequires a large amount of computing power.
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Fusing Matching
A variety of combination rules have been proposed. Ithas shown that matching accuracy can be improved
by combining independent matchers using Neyman –
Pearson rule. Here, we will also use Neyman – Pearson
rule for the task.
Matching of test fingerprint with template is done in
Neyman-Pearson rule. Two sets of minutiae are
compared. If matching score is found, then thefingerprint is matched with template. Otherwise does
not matched with the template.
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Input And Output Screens
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Main Page
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Authentication
L d BMP I
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Load BMP Image
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Extract Template
Enroll
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Enroll
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R t
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Reports
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Verify
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Verify
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Verify
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Verify
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Identify
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Identify
ClearDatabase
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Clear Database
Clear Log
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g
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Benefits of the project
The project can be used for security purposes.
E.g. : Attendance ,voter registration,
Crime Investigation,
forensic fingerprint searching.
CONCLUSION
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CONCLUSIONOrientation field is important for fingerprint
representation. In order to utilize the orientationinformation in automatic fingerprint recognition
systems which only stores minutiae feature. So we can
reduce the usage of memory and enhancing the
performance of system.
We also utilize the reconstructed orientation field
information into the matching stage. We can reducethe effect of wrongly detected minutiae. A fingerprint
matching based on orientation field is used to combine
with conventional minutiae matching for real
applications.
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THANK YOU