Fingerprint Recognition
Checkpoint Slides
Andrew Ackerman
Professor Ostrovsky
Current State
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Already Done
Research Fingerprint Acquiring
 Research Fingerprint Analyzing
 Research Fingerprint Recognition Algorithms
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Including Minutiae detection and learned based templates
Current State
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Reduced Fingerprint Recognition to Another
Problem
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Solving for algorithm for problem
Fingerprint Recognition
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Taking two fingerprint images and seeing if they come
from the same finger
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Assumption: no two fingers in the world yield the same
fingerprint and that fingerprints do not change in time
Much research has been done to validate these assumptions
Complex
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Due to a multitude of conditions the same fingerprint
scanned twice can look very different
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How finger is oriented on scanner
Condition of finger (wet, dry, scarred, etc)
No completely accurate method exists
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Many current recognition techniques can tell with a degree of
certainty if two fingerprint images match (i.e. come from same finger)
Our Method
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First try
View the fingerprint edges as a graph structure.
 Bifurcation and ending points would become nodes
and the edges would be edges
 Abandoned due to complexity involved in matching
sub graphs of two different graphs
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Currently Explored Method
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Reduce fingerprint recognition into a problem of
topographical equivalence
Reduced Problem
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Topological Equivalence
Ridges of the fingerprint are just lines that when
leave the frame of view go off to infinity
 If two fingerprints can be shown to be nearly
topologically equivalent then they are most likely the
same fingerprint
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Topological Equivalence
Topologically Equivalent
Not Topologically Equivalent
Two images are topologically equivalent if you can
somehow deform the lines (without crossing
them over) to go from one image to the other
Current Goal
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Come up with an algorithm that can determine
topological equivalence for relatively simple
cases, then generalize to reach most of the cases
required for the fingerprint recognition.
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Mainly dealing with shapes that include bifurcations
and edges and possibly loops
Write software that implements the algorithm
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Will use NIST Special Database 4 (fingerprint
database) to test algorithm
Self Assessment
I feel that I have not done all the work I could possibly have
accomplished in the fall quarter. However, as I noted at the
beginning to Professor Sahai, I had a heavy course load with
courses such as CS152B and graduate school applications.
With these out of the way for next quarter, I will have much
more time to dedicate to coding for CS194.
That being said, both Professor Ostrovsky and I feel we are
on track to receive good results by the end of the spring
quarter. The best case scenario being that our algorithm
performs faster and/or more accurately then current
algorithms used.
Self Assessment
Our main project focus has changed. The cryptology
part of the project has been dropped for now and the
main focus is on fingerprint recognition. I feel a good
amount of work has been done on understanding some
of the current algorithms for fingerprint recognition.
And our current focus is to develop and code our own
algorithm to test them.
Overall, I feel I have done adequate amount of work
for CS 194 during the fall quarter. And I plan to get a
good amount of work done over winter break
regarding our algorithm and coding it.