Recompression effects in iris recognition

• Published in: Image and vision computing Vol. 58; pp. 142 - 157
• Main Authors: Bergmüller, Thomas, Christopoulos, Eleftherios, Fehrenbach, Kevin, Schnöll, Martin, Uhl, Andreas
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.02.2017
• Subjects: Image compression; Image quality; Iris recognition; Iris segmentation; ISO standards; Recompression; Image quality; Image compression; Recompression; ISO standards; Iris segmentation; Iris recognition
• ISSN: 0262-8856; 1872-8138
• DOI: 10.1016/j.imavis.2016.08.003

Rating a compression algorithms' performance is usually done in experimental studies, where researchers have frequently used JPEG pre-compressed data. It is not clear yet, if results of such compression experiments are reliable when conducted on pre-compressed data. To investigate this issue, we first study the impact of using pre-compressed data in iris segmentation and evaluate the relation between iris segmentation performance and general image quality metrics. In this context we propose a method to overcome potential problems in case using pre-compressed data sets cannot be avoided. As the second step, we conduct experimentation on the entire iris recognition pipeline. We find that overall, recognition accuracy results might not be entirely reliable in case of applying JPEG XR or JPEG2000 to JPEG pre-compressed data. •Investigate the influence on using pre-compressed original data in compression experiments.•We find that iris segmentation and iris recognition accuracy are influenced.•Image quality metrics may serve as a rough guideline describing general effects.•Recognition accuracy results are not entirely reliable for heterogeneous recompression.