Effects of Sampling and Compression on Human IRIS Verification

Custom JPEG Quantization for Improved Iris Recognition Accuracy

“…The claim that compression up to a rate of 16 even improves the matching scores of not compressed images [11] can be supported at least for the 2 compressed images case and the STQ, for "better" Q-tables this is correct even up to compression rate 20 and higher.…”

“…Note that it makes an important difference if compression is applied to rectangular or polar iris images which has an important implication on the performance of the entire system. Whereas in the case of compressing polar iris images [11] only the iris texture information is affected, in the case of compressing rectangular image data also the iris detection and determination of the noise mask is potentially affected in addition to degrading texture information. Figure 3 shows an example of a JPEG2000 compressed (compression rate 96) iris image of one person, together with the extracted iris template data and the noise masks (template and noise mask have been scaled in y-direction by a factor of 4 for proper display).…”

“…Ives et al [5,6] apply JPEG2000 up to a compression rate of 20 to rectilinear image data (the CASIA database and a proprietary image collection is used) and investigates the effects on FAR and FRR of a 1-D version of the Daugman algorithm (the same system which is used in this study). Rakshit and Monro [11] again use JPEG2000 to compress polar iris images up to a compression rate of 80 and studies the impact on verification accuracy of three iris recognition systems (including the Daugman algorithm, the CASIA database is used). Daugman and Downing [3] apply JPEG and JPEG2000 to rectilinear image data (the NIST ICE database is used) and remove image background (i.e.…”

Comparison of Compression Algorithms’ Impact on Iris Recognition Accuracy

“…This has an important implication on the performance of the entire system. Whereas in the case of compressing polar iris images [9] only the iris texture information is affected, in the case of compressing rectangular image data also the iris detection and determination of the noise mask is potentially affected in addition to degrading texture information. Figure 1 shows an example of a JPEG2000 compressed (compression rate 96) iris image of one person, which was used in our calculations together with the extracted iris template data and the noise masks (template and noise mask have been scaled in y-direction by a factor of 4 for proper display).…”

“…[10] applies JPEG2000 up to a compression rate of 20 to rectilinear image data (the CASIA database and a proprietary image collection is used) and investigates the effects on FAR and FRR of a 1-D version of the Daugman algorithm (the same system which is used in this study). [9] again uses JPEG2000 to compress polar iris images up to a compression rate of 80 and studies the impact on verification accuracy of three iris recognition systems (including the Daugman algorithm, the CASIA database is used). A more compact way of representing the Daugman IrisCode is discussed in [12], however, these results refer to template compression and are only valid for the techniques related to Iridian products.…”