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Does lossy image compression affect racial bias within face recognition?

Yucer, S. and Poyser, M. and Al Moubayed, N. and Breckon, T.P. (2022) 'Does lossy image compression affect racial bias within face recognition?', International Joint Conference on Biometrics (IJCB 2022) Abu Dhabi, UAE, 10-13 Oct 2022.


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.

Item Type:Conference item (Paper)
Full text:(AM) Accepted Manuscript
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Publisher statement:© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Date accepted:25 July 2022
Date deposited:19 August 2022
Date of first online publication:2022
Date first made open access:14 October 2022

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