Combining Fingerprint Classifiers

Authors:
Raffaele Cappelli;Dario Maio;Davide Maltoni
Affiliations:
-;-;-
Venue:
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Year:
2000

Citing 8
Cited 6

Fingerprint pattern classification

Pattern Recognition
Introduction to statistical pattern recognition (2nd ed.)

Introduction to statistical pattern recognition (2nd ed.)
Continuous versus exclusive classification for fingerprint retrieval

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A Multichannel Approach to Fingerprint Classification

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Classification by Directional Image Partitioning

IEEE Transactions on Pattern Analysis and Machine Intelligence
Expert Conciliation for Multi Modal Person Authentication Systems by Bayesian Statistics

AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication
A Structural Approach to Fingerprint Classification

ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Combining Classifiers

ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2

Information Fusion in Biometrics

AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Fingerprint Classification by Combination of Flat and Structural Approaches

AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Recent Advances in Fingerprint Verification

AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Residual orientation modeling for fingerprint enhancement and singular point detection

Pattern Recognition
Cascading a couple of registration methods for a high accurate fingerprint verification system

SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Statistical Normalization techniques for the prediction of COD level for an anaerobic wastewater treatment plant

Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology

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Abstract

This paper explores several ways of combining the MASKS and MKL-based classifiers which we specifically designed for the fingerprint classification task. The advantages of coupling these distinct techniques are well evident; in particular, in the case of exclusive classification, the FBI challenge requiring a classification error ≤1% at 20% rejection was broken on NIST-DB14.