6533b832fe1ef96bd129ad76

RESEARCH PRODUCT

A Novel Technique for Fingerprint Classification based on Fuzzy C-Means and Naive Bayes Classifier

G. I. M. MiglioreFilippo SorbelloGiuseppe VitelloSalvatore VitabileVincenzo Conti

subject

Novel techniqueSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryPattern recognitioncomputer.software_genreClass (biology)Fuzzy logicImage (mathematics)Set (abstract data type)Naive Bayes classifierFingerprintKey (cryptography)Artificial intelligenceData miningbusinessFingerprint Classification Directional Images Fuzzy C-Means Naive Bayes Classifiercomputer

description

Fingerprint classification is a key issue in automatic fingerprint identification systems. One of the main goals is to reduce the item search time within the fingerprint database without affecting the accuracy rate. In this paper, a novel technique, based on topological information, for efficient fingerprint classification is described. The proposed system is composed of two independent modules: the former module, based on Fuzzy C-Means, extracts the best set of training images, the latter module, based on Fuzzy C-Means and Naive Bayes classifier, assigns a class to each processed fingerprint using only directional image information. The proposed approach does not require any image enhancement phase. Experimental trials, conducted on a subset of the free downloadable PolyU database, show a classification rate of 91% over a 100 images test database using only 12 training examples.

yearjournalcountryeditionlanguage
2014-07-01
10.1109/cisis.2014.23http://hdl.handle.net/10447/100570