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
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
Theoretical Computer Science
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Digital Image Processing
Fingerprint image enhancement using filtering techniques
Real-Time Imaging
Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
A modified Gabor filter design method for fingerprint image enhancement
Pattern Recognition Letters
Automatic Fingerprint Recognition Systems
Automatic Fingerprint Recognition Systems
Fingerprint classification: a review
Pattern Analysis & Applications
A novel evolutionary approach to image enhancement filter design: method and applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Automatic fingerprints image generation using evolutionary algorithm
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Automatic fingerprints image generation using evolutionary algorithm
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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Singularity is the special feature of fingerprints for identification and classification. Since the performance of singularity extraction depends on the quality of fingerprint images, image enhancement is required to improve the performance. Image enhancement with various image filters might be more useful than a filter, but it is very difficult to find a set of appropriate filters. In this paper, we propose a method that uses the genetic algorithm to find those filters for superior performance of singularity extraction. The performance of the proposed method has been verified by the experiment with NIST DB 4. Moreover, the proposed method does not need any expert knowledge to find the type and order of filters for the target domain, it can be easily applied to other applications of image processing.