Fingerprint Matching Based on Neighboring Information and Penalized Logistic Regression
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Reconstructing orientation field from fingerprint minutiae to improve minutiae-matching accuracy
IEEE Transactions on Image Processing
Robust orientation field estimation and extrapolation using semilocal line sensors
IEEE Transactions on Information Forensics and Security - Special issue on electronic voting
Proceedings of the 2010 Symposium on Information and Communication Technology
Fingerprint recognition based on combined features
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Fast fingerprint alignment method based on minutiae orientation histograms
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
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As an important feature, orientation field describes the global structure of fingerprints. It provides robust discriminatory information other than traditional widely-used minutiae points. However, there are few works explicitly incorporating this information into fingerprint matching stage, partly due to the difficulty of saving the orientation field in the feature template. In this paper, we propose a novel representation for fingerprints which includes both minutiae and model-based orientation field. Then, fingerprint matching can be done by combining the decisions of the matchers based on the global structure (orientation field) and the local cue (minutiae). We have conducted a set of experiments on large-scale databases and made thorough comparisons with the state-of-the-arts. Extensive experimental results show that combining these local and global discriminative information can largely improve the performance. The proposed system is more robust and accurate than conventional minutiae-based methods, and also better than the previous works which implicitly incorporate the orientation information. In this system, the feature template takes less than 420 bytes, and the feature extraction and matching procedures can be done in about 0.30 s. We also show that the global orientation field is beneficial to the alignment of the fingerprints which are either incomplete or poor-qualitied.