A new approach for fingerprint verification, based on wavelets and pseudo Zernike moments (PZMs), is

discussed. PZMs are robust to noisy images, invariant to rotation and have a good image reconstruction

capability [4]. PZMs have been used for global analysis and so they are used to extract global features (the

shape of the fingerprint image). Wavelets are good at local analysis and so they help to extract local

features (minutiae) from a fingerprint. Therefore, this hybrid approach extracts most significant features

from the fingerprint images and achieve better verification rate. Different types of wavelets are used for the

study but the result shows that Symmlet orthonormal wavelet of order 8 gives best verification rate.