Comparison of compression algorithms impact on fingerprint and face recognition accuracy The impact of using different lossy compression algorithms on the matching accuracy of fingerprint and face recognition systems is investigated. In particular, we relate ratedistortion performance as measured in PSNR to the matching scores as obtained by the recognition systems. JPEG2000 and SPIHT are correctly predicted by PSNR to be the most suited compression algorithms to be used in fingerprint and face recognition systems. Fractal compression is identified to be least suited for the use in the investigated recognition systems, although PSNR suggests JPEG to deliver worse recognition results in the case of face imagery. JPEG compression performs surprisingly well at high bitrates in face recognition systems, given the low PSNR performance observed.

JPEG2000 Part 2 Wavelet Packet Subband Structures in Fingerprint Recognition The impact of using different wavelet packet subband structures in JPEG2000 on the matching accuracy of a fingerprint recognition system is investigated. In particular, we relate ratedistortion performance as measured in PSNR to the matching scores as obtained by the recognition system. Employing wavelet packets instead of the dyadic wavelet transform turns out to be of advantage only in case of low bitrates (i.e. high compression rates). For such settings, the good performance of the WSQ structure is confirmed also in JPEG2000 and in particular we get better recognition accuracy using the WSQ structure as compared to the employment of a ratedistortion optimising subband selection approach.