Evolutionary Singularity Filter Bank Optimization for Fingerprint Image Enhancement

摘要

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.