Use of Quality Measures for Rural Indian Fingerprint Image Database Enhancement and Improve the Recognition Rate

Identification and authentication is done using various biometric sign like fingerprints. The recognition rate of correct person is depending on quality of fingerprints images. Fingerprints quality also varying from rural and urban population. Rural population having more physical work than urban population. Therefore the ridges, valleys, bifurcation, joints, minutia etc. features are not good quality hence it reduces recognition rate accuracy. To improve recognition rate of such images there is strong need to first improve the quality of features. In this paper used the rural fingerprints database which is collected from IIIT Delhi research lab which consists of 1632 fingerprints images. Out of which preprocess 100 sample images using histogram equalization and tried to improve the quality of images. The resultant images quality is verified by using different quality measures like PSNR, MSE, MAXERR, L2RAT, it is found that quality has been improved. Hence it is proved that the recognition rate is increases.