  In this paper, we propose an efficient method to provide personal
identification using fingerprint to get better accuracy even in noisy
condition. The fingerprint matching based on the number of corresponding
minutia pairings, has been in use for a long time, which is not very efficient
for recognizing the low quality fingerprints. To overcome this problem,
correlation technique is used. The correlation-based fingerprint verification
system is capable of dealing with low quality images from which no minutiae can
be extracted reliably and with fingerprints that suffer from non-uniform shape
distortions, also in case of damaged and partial images. Orientation Field
Methodology (OFM) has been used as a preprocessing module, and it converts the
images into a field pattern based on the direction of the ridges, loops and
bifurcations in the image of a fingerprint. The input image is then Cross
Correlated (CC) with all the images in the cluster and the highest correlated
image is taken as the output. The result gives a good recognition rate, as the
proposed scheme uses Cross Correlation of Field Orientation (CCFO = OFM + CC)
for fingerprint identification.
