'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
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