by A Almansa, L Cohen
Abstract:
A common approach in fingerprint matching algorithms consists of minimizing a similarity measure between feature vectors of both images, over a set of linear transformations of one image to the other. In this work we propose the thin-plate spline as a more accurate model for the geometric transformations that arise in fingerprint images. In addition we show how such a model can be integrated into a matching algorithm by means of a two-step iterative minimization with auxiliary variables. Such a method allows to correct many of the false pairings of minutiae commonly found by matching algorithms based on linear transforms
Reference:
Fingerprint image matching by minimization of a thin-plate energy using a two-step algorithm with auxiliary variables (A Almansa, L Cohen), In (WACV 2000) Proceedings Fifth IEEE Workshop on Applications of Computer Vision, IEEE Comput. Soc, 2000.
Bibtex Entry:
@inproceedings{Almansa2000,
Abstract = {A common approach in fingerprint matching algorithms consists of minimizing a similarity measure between feature vectors of both images, over a set of linear transformations of one image to the other. In this work we propose the thin-plate spline as a more accurate model for the geometric transformations that arise in fingerprint images. In addition we show how such a model can be integrated into a matching algorithm by means of a two-step iterative minimization with auxiliary variables. Such a method allows to correct many of the false pairings of minutiae commonly found by matching algorithms based on linear transforms},
Author = {Almansa, A and Cohen, L},
Booktitle = {(WACV 2000) Proceedings Fifth IEEE Workshop on Applications of Computer Vision},
Doi = {10.1109/WACV.2000.895400},
Isbn = {0-7695-0813-8},
Pages = {35--40},
Publisher = {IEEE Comput. Soc},
Title = {{Fingerprint image matching by minimization of a thin-plate energy using a two-step algorithm with auxiliary variables}},
Year = {2000},
Bdsk-Url-1 = {https://doi.org/10.1109/WACV.2000.895400}}