FINGERPRINT VERIFICATION SYSTEM USING PRINCIPALCOMPONENT TRANSFORMATION EIGENVECTORS TECHNIQUE

Abstract

A fingerprint verification technique is presented. The Principal Component
Transformation “PCT” is used to identify a checked person, by comparing its
eigenvector with the PCT eigenvectors of stored fingerprints images in a Database.
The computed Eigenvectors of the input images are determined from the covariance
matrix of the set of fingerprints reduced mean images which were ascended as
column vectors in a two dimensional array. The covariance matrix then determined
by multiplying the mean (i.e. average) reduced matrix by its transpose. The
similarity between the stored images of the fingers (as Database) and the test finger
is presented by utilizing the Minimum Mean Square Error (MMSE) criterion.