Effects of severe image compression on iris segmentation performance

The International Organization for Standardization (ISO) specifies iris biometric data to be recorded and stored in (raw) image form (ISO/IEC 19794-6), rather than in extracted templates, i.e. iris-codes. Existing literature confirms the applicability of lossy image compression in iris biometric systems, however, so far investigations on the impact of image compression on iris segmentation algorithms have remained elusive. In this work we examine the impact of severe image compression algorithms in particular, JPEG, JPEG 2000, and JPEG-XR, on the performance of different iris segmentation approaches. Experiments are carried out on an uncompressed iris database and, based on a manually annotated ground truth, effects of image compression on iris segmentation are quantified. It is found that surprisingly, JPEG causes the least segmentation errors over a wide range of high to medium bitrates (down to 0.3 bpp) despite of its weak performance in terms of PSNR rate-distortion behaviour.