Fingerprint classification based on Adaboost learning from singularity features
Pattern Recognition
A fingerprint retrieval system based on level-1 and level-2 features
Expert Systems with Applications: An International Journal
Fingerprint indexing with bad quality areas
Expert Systems with Applications: An International Journal
Indexing and retrieving in fingerprint databases under structural distortions
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
This paper proposes an approach of fingerprint retrieval based on the continuous classification of two complex filter responses. Two complex filters are introduced and applied on the fingerprint orientation field to extract the local singularities, the similarities to the singular points. A numerical feature vector from the aligned fingerprint local singularities is constructed as the global feature for fingerprint retrieval. The continuous classification is employed to retrieve a subset of fingerprints similar to the query fingerprint for the finer matching. Experimental results on NIST fingerprint database 4 (NIST-4) show the effectiveness of the proposed fingerprint retrieval approach.