Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
A Real-Time Matching System for Large Fingerprint Databases
IEEE Transactions on Pattern Analysis and Machine Intelligence
On-Line Fingerprint Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Image Enhancement: Algorithm and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
FVC2000: Fingerprint Verification Competition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
On the Individuality of Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct Gray-Scale Minutiae Detection In Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Memetic Algorithms and the Fitness Landscape of the Graph Bi-Partitioning Problem
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
FVC2002: Second Fingerprint Verification Competition
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Fingerprint Matching Using an Orientation-Based Minutia Descriptor
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational Algorithms for Fingerprint Recognition (Kluwer International Series on Biometrics, 1)
Computational Algorithms for Fingerprint Recognition (Kluwer International Series on Biometrics, 1)
Evolutionary Computation - Special issue on magnetic algorithms
A minutia-based partial fingerprint recognition system
Pattern Recognition
Fingerprint matching based on global alignment of multiple reference minutiae
Pattern Recognition
Filterbank-based fingerprint matching
IEEE Transactions on Image Processing
Fingerprint registration by maximization of mutual information
IEEE Transactions on Image Processing
Fingerprint recognition using model-based density map
IEEE Transactions on Image Processing
Directional filter bank-based fingerprint feature extraction and matching
IEEE Transactions on Circuits and Systems for Video Technology
Fingerprint matching with an evolutionary approach
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Proceedings of the 2010 Symposium on Information and Communication Technology
Engineering Applications of Artificial Intelligence
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Fingerprint matching has been approached using various criteria based on different extracted features. However, robust and accurate fingerprint matching is still a challenging problem. In this paper, we propose an improved integrated method which operates by first suggesting a consensus matching function, which combines different matching criteria based on heterogeneous features. We then devise a genetically guided approach to optimise the consensus matching function for simultaneous fingerprint alignment and verification. Since different features usually offer complementary information about the matching task, the consensus function is expected to improve the reliability of fingerprint matching. A related motivation for proposing such a function is to build a robust criterion that can perform well over a variety of different fingerprint matching instances. Additionally, by employing the global search functionality of a genetic algorithm along with a local matching operation for population initialisation, we aim to identify the optimal or near optimal global alignment between two fingerprints. The proposed algorithm is evaluated by means of a series of experiments conducted on public domain collections of fingerprint images and compared with previous work. Experimental results show that the consensus function can lead to a substantial improvement in performance while the local matching operation helps to identify promising initial alignment configurations, thereby speeding up the verification process. The resulting algorithm is more accurate than several other proposed methods which have been implemented for comparison.