Does lossy image compression affect racial bias within face recognition?

Yucer, S.; Poyser, M.; Al Moubayed, N.; Breckon, T.P.

Abstract

This study investigates the impact of commonplace lossy image compression on face recognition algorithms with regard to the racial characteristics of the subject. We adopt a recently proposed racial phenotype-based bias analysis methodology to measure the effect of varying levels of lossy compression across racial phenotype categories. Additionally, we determine the relationship between chroma-subsampling and race-related phenotypes for recognition performance. Prior work investigates the impact of lossy JPEG compression algorithm on contemporary face recognition performance. However, there is a gap in how this impact varies with different race-related inter-sectional groups and the cause of this impact. Via an extensive experimental setup, we demonstrate that common lossy image compression approaches have a more pronounced negative impact on facial recognition performance for specific racial phenotype categories such as darker skin tones (by up to 34.55%). Furthermore, removing chromasubsampling during compression improves the false matching rate (up to 15.95%) across all phenotype categories affected by the compression, including darker skin tones, wide noses, big lips, and monolid eye categories. In addition, we outline the characteristics that may be attributable as the underlying cause of such phenomenon for lossy compression algorithms such as JPEG.

Citation

Yucer, S., Poyser, M., Al Moubayed, N., & Breckon, T. (2022, October). Does lossy image compression affect racial bias within face recognition?. Presented at International Joint Conference on Biometrics (IJCB 2022), Abu Dhabi, UAE

• Presentation Conference Type: Conference Paper (published)
• Conference Name: International Joint Conference on Biometrics (IJCB 2022)
• Start Date: Oct 10, 2022
• End Date: Oct 13, 2022
• Acceptance Date: Jul 25, 2022
• Publication Date: 2022-10
• Deposit Date: Aug 18, 2022
• Publicly Available Date: Oct 14, 2022
• Publisher: Institute of Electrical and Electronics Engineers
• Public URL: https://durham-repository.worktribe.com/output/1137138
• Publisher URL: https://ieeexplore.ieee.org/xpl/conhome/1842444/all-proceedings