A Model-Based Method for the Computation of Fingerprints' Orientation Field
- 18 May 2004
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Image Processing
- Vol. 13 (6), 821-835
- https://doi.org/10.1109/tip.2003.822608
Abstract
As a global feature of fingerprints, the orientation field is very important for automatic fingerprint recognition. Many algorithms have been proposed for orientation field estimation, but their results are unsatisfactory, especially for poor quality fingerprint images. In this paper, a model-based method for the computation of orientation field is proposed. First a combination model is established for the representation of the orientation field by considering its smoothness except for several singular points, in which a polynomial model is used to describe the orientation field globally and a point-charge model is taken to improve the accuracy locally at each singular point. When the coarse field is computed by using the gradient-based algorithm, a further result can be gained by using the model for a weighted approximation. Due to the global approximation, this model-based orientation field estimation algorithm has a robust performance on different fingerprint images. A further experiment shows that the performance of a whole fingerprint recognition system can be improved by applying this algorithm instead of previous orientation estimation methods.Keywords
This publication has 23 references indexed in Scilit:
- FVC2000: fingerprint verification competitionIEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
- A multichannel approach to fingerprint classificationIEEE Transactions on Pattern Analysis and Machine Intelligence, 1999
- Orientation diffusionsIEEE Transactions on Image Processing, 1998
- Fingerprint matching using transformation parameter clusteringIEEE Computational Science and Engineering, 1997
- A nonlinear orientation model for global description of fingerprintsPattern Recognition, 1996
- Fingerprint classificationPattern Recognition, 1996
- Statistical Analysis of Circular DataPublished by Cambridge University Press (CUP) ,1993
- A model for interpreting fingerprint topologyPattern Recognition, 1993
- An approach to fingerprint filter designPattern Recognition, 1989
- Fingerprint pattern classificationPattern Recognition, 1984