Fingerprint Verification Based on STFT Analysis and Zernike Moments

This paper presents a scheme of fingerprint verification based using Zernike invariant moments. In this study we uses an enhanced image-based fingerprint verification algorithm .Itreduces multi-spectral noise by enhancing a fingerprint image to accurately and reliably determine a reference point, and thenaligns the image according to the position and orientation of reference point to avoid time-consuming alignment. A set of fixed-length moment features, is extracted from tessellated cellson a region of interest (ROI) centered at the reference point. After determination the ROI, Zernike moments were computedfrom each block of ROI as the feature of fingerprint features. The similarity between an input and a template in a database isevaluated by K-NN classifier. The proposed scheme can improve performance of verification and is more robust with respect tothe fingerprint image quality

کلیدواژه ها:

component ، Fingerprint Verification ، STFT analysis ، Feature Extraction ، Zernike moments ، K-NN classifiers