A model-based method for the computation of fingerprints' orientation field

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...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on image processing Vol. 13; no. 6; pp. 821 - 835
Main Authors: Zhou, J., Gu, J.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.06.2004
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Applied sciences
Approximation
Approximation algorithms
Artificial Intelligence
Automation
Bifurcation
Biometrics
Cluster Analysis
Computation
Computer Graphics
Computer Simulation
Dermatoglyphics
Exact sciences and technology
Fingerprint recognition
Fingerprints
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image matching
Image processing
Information Storage and Retrieval - methods
Information, signal and communications theory
Large-scale systems
Mathematical analysis
Mathematical models
Models, Biological
Models, Statistical
Numerical Analysis, Computer-Assisted
Orientation
Pattern Recognition, Automated - methods
Polynomials
Reproducibility of Results
Robustness
Sensitivity and Specificity
Signal processing
Signal Processing, Computer-Assisted
Studies
Subtraction Technique
Telecommunications and information theory
global approximation
Fingerprint
Image recognition
Approximation
Singular point
orientation field
Orientation
Automatic recognition
Automatic fingerprint recognition
combination model
ISSN:1057-7149, 1941-0042
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ObjectType-Article-2
ObjectType-Feature-1
content type line 23
ObjectType-Undefined-3
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2003.822608