Integrated Wavelet and Fourier-Mellin invariant feature in fingerprint verification system

Abstract

Today, minutiae-based and image-based are the two major approaches for the purpose of fingerprint authentication. Image based approach offers much higher computation efficiency with minimum pre-processing and proves also effective even when the image quality is too low to allow a reliable minutia extraction. However, this approach is vulnerable to shape distortions as well as variation in position, scale and orientation angle. In this paper, a novel method of image based fingerprint matching based on the features extracted from the integrated Wavelet and the Fourier-Mellin Transform (WFMT is proposed. Wavelet transform is used to smooth and preserve the local edges after image decomposition, and hence making the fingerprint images less sensitive to shape distortion whilst Fourier-Mellin transform served to produce a translation, rotation and scale invariant feature. Multiple WFMT features can be used to form a reference invariant feature through the linearity property of Fourier-Mellin Transform and hence reduce the variability of the input fingerprint images. The experiments show the verification accuracy is over 96% and 99% of verification rate is achieved when multiple WFMT features are used.