Best parameter based compression of fingerprints with wavelet packets
by Gulzar A. Khuwaja
International Journal of Computer Applications in Technology (IJCAT), Vol. 19, No. 1, 2004

Abstract: Fingerprints are imprints formed by friction ridges of the skin in fingers and thumbs. Fingerprint recognition remains as one of the most prominent biometric identification methods. However, storage of fingerprint image databases needs allocation of huge secondary storage devices. To reduce the increasing demand on storage space, efficient data compression techniques are badly needed In addition to that, the exchange of fingerprint images between governmental agencies could be done fast. The compression algorithm must also preserve original information in the original image. This paper discovers the best design parameters for a data compression scheme applied to fingerprint images. The proposed technique aims at reducing the transmission cost while preserving the person's identity. By selecting the wavelet packet’s filters, decomposition level, and subbands that are better adapted to the frequency characteristics of the image, one may achieve better image representation in the sense of lower entropy or minimum distortion. Empirical results show that the selection of the best parameters has a dramatic effect on the data compression rate of fingerprint images. Statistical significance test is performed on the experimental measures to conduct the most suitable wavelet shape for fingerprint images. Image quality measures such as mean square error and peak signal-to-noise ratio are used to evaluate the performance of different wavelet filters.

Online publication date: Wed, 08-Oct-2003

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