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A Robust Two Step Approach
for Fingerprint Identification
Presented by: Xuejun Tan
ABSTRACT:
Due to the complex distortions involved in two impressions
of the same finger, fingerprint identification is still a
challenging problem. In this paper, we propose a two step
fingerprint identification approach based on the triplets
of minutiae. The features that we use to find the potential
corresponding triangles include angles, triangle orientation,
triangle direction, maximum side, minutiae density and ridge
counts. In the first step, based on the number of corresponding
triangles between the query fingerprint and the model database
constructed offline, hypotheses are generated.
In the second step, called verification, false corresponding
triangles are eliminated by applying constraints to the transformation
between two potential corresponding triangles. The experimental
results on National Institute of Standards and Technology
special fingerprint database 4, NIST-4, show that the proposed
approach provides a reduction by a factor of 200 for the number
of the hypotheses that need to be considered if linear search
is used and can achieve a good performance even when a large
portion of fingerprints in the database are of poor quality.
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