Paper Info
Title
Elastic minutiae matching by means of thin-plate spline models
Abstract
This paper presents a novel minutiae matching method that deals with elastic distortions by normalizing the shape of the test fingerprint with respect to the template. The method first determines possible matching minutiae pairs by means of comparing local neighborhoods of the minu- tiae. Next a thin-plate spline model is used to describe the non-linear distortions between the two sets of possible pairs. One of the fingerprints is deformed and registered according to the estimated model, and then the number of matching minutiae is counted. This method is able to deal with all possible non-linear distortions while using very tight bounding boxes. For deformed fingerprints, the algo- rithm gives considerably higher matching scores compared to rigid matching algorithms, while only taking 100 ms on a 1 GHz P-III machine.
Year
DOI
Venue
2002
10.1109/ICPR.2002.1048471
Pattern Recognition, 2002. Proceedings. 16th International Conference  
Keywords
Field
DocType
fingerprint identification,image matching,image registration,nonlinear distortion,splines (mathematics),elastic distortions,elastic minutiae matching,fingerprint deformation,fingerprint matching,fingerprint registration,fingerprint shape normalization,local neighborhood comparison,matching scores,nonlinear distortions,template fingerprint,test fingerprint,thin-plate spline models,tight bounding boxes
Spline (mathematics),Computer vision,Thin plate spline,Pattern recognition,Minutiae,Computer science,Fingerprint recognition,Fingerprint,Artificial intelligence,Nonlinear distortion,Image registration,Bounding overwatch
Conference
Volume
ISSN
Citations 
2
1051-4651
13
PageRank 
References 
Authors
1.41
8
2
Name
Order
Citations
PageRank
a m bazen159047.26
Gerez, S.H.228629.37