The impact of using different lossless compression algorithms on the compression ratios and timings when processing various biometric sample data is investigated. In particular, we relate the application of lossless JPEG, JPEG-LS, lossless JPEG2000 and SPIHT, PNG, GIF, and a few general purpose compression schemes to imagery of the following biometric modalities: fingerprint, iris, retina, face, and hand. Results differing from behaviour found with common or textured imagery are specifically discussed.

Abstract. JPEG XR is considered as a lossy sample data compression scheme in the context of iris recognition techniques. It is shown that apart from low-bitrate scenarios, JPEG XR is competitive to the current standard JPEG2000 while exhibiting significantly lower computational demands.

Abstract. The impact of using different lossless compression algorithms when compressing biometric iris sample data from several public iris databases is investigated. In particular, the application of dedicated lossless image codecs (lossless JPEG, JPEG-LS, PNG, and GIF), lossless variants of lossy codecs (JPEG2000, JPEG XR, and SPIHT), and a few general purpose file compression schemes is compared. We specifically focus on polar iris images (as a result after iris detection, iris extraction, and mapping to polar coordinates). The results are discussed in the light of the recent ISO/IEC FDIS 19794-6 standard and IREX recommendations.

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