Comparison of compression algorithms' impact on iris recognition accuracy II: revisiting JPEG

Jenisch, Stefan; Lukesch, Stefan; Uhl, Andreas

doi:10.1117/12.766360

Cited by 21 publications

(4 citation statements)

References 6 publications

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“…We performed the tests for JPEG2000 coding with rates of 0.3, 0.2, 0.1 and 0.08 bits per pixel (bpp) on the CASIA image sets and coding rates of 0.8, 0.7,0.6 and 0.5 bpp for the UBIRIS image sets. Note that in the case of UBIRIS images, we apply a re-compression to JPEGcompressed imagery where results are different as compared to compressing raw image data [5]. We measure Hamming distance (HD) and plot on the y-axis 1 − HD as the matching score.…”

Section: Resultsmentioning

confidence: 99%

“…Five general purpose compression algorithms (including JPEG and JPEG2000) are compared in [6,5] with respect to their impact on iris recognition accuracy of three different recognition schemes (the CASIA and UBIRIS databases have been used). In accordance to [2] significantly superior compression performance of JPEG2000 over JPEG especially for low bitrates have been found.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improving Compressed Iris Recognition Accuracy Using JPEG2000 RoI Coding

Hämmerle-Uhl

Prahauser

Starzacher

et al. 2009

Advances in Biometrics

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The impact of using JPEG2000 region of interest coding on the matching accuracy of iris recognition systems is investigated. In particular, we compare the matching scores as obtained by a concrete recognition system when using JPEG2000 compression of rectilinear iris images with and without region of interest coding enabled. The region of interest is restricted to the iris texture area plus the pupil region. It turns out that average matching scores can be improved and that the number of false negative matches is significantly decreased using region of interest coding as compared to plain JPEG2000 compression.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improving Compressed Iris Recognition Accuracy Using JPEG2000 RoI Coding

Hämmerle-Uhl

Prahauser

Starzacher

et al. 2009

Advances in Biometrics

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“…However, iris recognition seems to be robust for image distortions resulting from image compression, as shown by Daugman et al [19], Jenisch et al [20], Rathgeb et al [21] and Grother et al [22].…”

Section: Past Workmentioning

confidence: 99%

Verification of iris image authenticity using fragile watermarking

Czajka

Kasprzak

Wilkowski

2016

Bulletin of the Polish Academy of Sciences Technical Sciences

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Abstract. This paper proposes and evaluates a watermarking-based approach to certify the authenticity of iris images when they are captured by a genuine equipment. In the proposed method, the iris images are secretly signed before being used in biometric processes, and the resulting signature is embedded into the JPEG carrier image in the DCT domain in a data-dependent way. Any alteration of the original (certified) image makes the signature no longer corresponding to this image and this change can be quickly identified at the receiver site. Hence, it is called fragile watermarking to differentiate this method from regular watermarking that should present some robustness against image alterations. There is no need to attach any auxiliary signature data, hence the existing, already standardized transmission channels and storage protocols may be used. The embedding procedure requires to remove some part of the original information. But, by using the BATH dataset comprising 32 000 iris images collected for 1 600 distinct eyes, we verify that the proposed alterations have no impact on iris recognition reliability, although statistically significant, small differences in genuine score distributions are observed when the watermark is embedded to both the enrollment and verification iris images. This is a unique evaluation of how the watermark embedding of digital signatures into the ISO CROPPED iris images (during the enrollment, verification or both) influences the reliability of a well-established, commercial iris recognition methodology. Without loss in generality, this approach is targeted to biometric-enabled ID documents that deploy iris data to authenticate the holder of the document.

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“…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. In previous work [9,7], we have compared five general purpose compression algorithms (including JPEG and JPEG2000) with respect to their impact on iris recognition accuracy of three different recognition schemes (the CASIA database has been used). In accordance to [3] superior compression performance of JPEG2000 over JPEG is found especially for low bitrates, however, for high and medium quality JPEG is still an option to consider.…”

Section: Iris Image Compressionmentioning

confidence: 99%