Fingerprint pattern classification
Pattern Recognition
Computer Vision, Graphics, and Image Processing
Segmentation of fingerprint images using the directional image
Pattern Recognition
Segmentation of fingerprint images—a composite method
Pattern Recognition
Fingerprint Image Enhancement: Algorithm and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Classification by Directional Image Partitioning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Synthetic Fingerprint-Image Generation
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Definition and extraction of stable points from fingerprint images
Pattern Recognition
Singular Points Detection Based on Zero-Pole Model in Fingerprint Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel fingerprint singular point detection algorithm
CEA'09 Proceedings of the 3rd WSEAS international conference on Computer engineering and applications
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
Registration of fingerprints by complex filtering and by 1d projections of orientation images
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Singular points analysis in fingerprints based on topological structure and orientation field
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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Singular points of a fingerprint are considered important global features. They are useful for fingerprint classification and matching because they can reduce the search time and space in large fingerprint databases and can also be regarded as reference points for fingerprint matching. In this paper, we implement a Poincaré Index based approach to detect singular points. Though Poincaré index approach can detect all true ground singular points, it also detects a number of spurious singular points. We use two techniques to remove spurious singular points, one of which is segmentation and the other is smoothing the orientation field of a fingerprint image. We propose a rule based approach to further remove spurious singular points. The experimental results show that our approach achieves total error rate of 8.46% on FVC 2002 databases.