Fingerprint Image Postprocessing Using Windowing Technique

Authors:
Anam Tariq;M. Usman Akram;Sarwat Nasir;Rabia Arshad
Affiliations:
Department of Computer Engineering, College of Electrical and Mechanical Engineering, National University of Science & Technology, Rawalpindi, Pakistan;Department of Computer Engineering, College of Electrical and Mechanical Engineering, National University of Science & Technology, Rawalpindi, Pakistan;Department of Telecommunication, College of Signals, National University of Science & Technology, Rawalpindi, Pakistan;Department of Computer Engineering, College of Electrical and Mechanical Engineering, National University of Science & Technology, Rawalpindi, Pakistan
Venue:
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Year:
2008

Citing 4
Cited 1

Fingerprint Image Enhancement: Algorithm and Performance Evaluation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Minutiae: A Constructive Definition

ECCV '02 Proceedings of the International ECCV 2002 Workshop Copenhagen on Biometric Authentication
Handbook of Fingerprint Recognition

Handbook of Fingerprint Recognition
A Study on Image Enhancement Techniques for Fingerprint Identification

AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance

Fingerprint image processing and fuzzy vault implementation

Journal of Mobile Multimedia

Quantified Score

Hi-index	0.00

Visualization

Abstract

Performance of Automatic Fingerprint Identification System (AFIS) is greatly affected by its matching rate, means it should have low False Acceptance Rate (FAR) and False Rejection Rate (FRR). Minutiae based fingerprint matching techniques are normally used for fingerprint matching. In this paper, we present a new technique for fingerprint image postprocessing. This postprocessing is used to eliminate a large number of false extracted minutiae from skeletonized fingerprint images. We propose a windowing postprocessing method that takes into account the neighborhood of each minutia within defined window and check for minutia validation and invalidation. The results are confirmed by visual inspections of validated minutiae of the FVC2004 reference fingerprint image database. Experimental results obtained by the proposed approach show efficient reduction of false minutiae.