Comparative study of features for fingerprint indexing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Invariant representation of orientation fields for fingerprint indexing
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
Dynamic discriminant functions with missing feature values
Pattern Recognition Letters
Fingerprint orientation field reconstruction by weighted discrete cosine transform
Information Sciences: an International Journal
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This paper presents a front-end filtering algorithm for fingerprint identification, which uses orientation field and dominant ridge distance as retrieval features. We propose a new distance measure that better quantifies the similarity evaluation between two orientation fields than the conventional Euclidean and Manhattan distance measures. Furthermore, fingerprints in the data base are clustered to facilitate a fast retrieval process that avoids exhaustive comparisons of an input fingerprint with all fingerprints in the data base. This makes the proposed approach applicable to large databases. Experimental results on the National Institute of Standards and Technology data base-4 show consistent better retrieval performance of the proposed approach compared to other continuous and exclusive fingerprint classification methods as well as minutia-based indexing schemes