Demographic Variability in Face Image Quality Measures
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866929675276648448 |
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| author | Kabbani, Wassim Raja, Kiran Ramachandra, Raghavendra Busch, Christoph |
| author_facet | Kabbani, Wassim Raja, Kiran Ramachandra, Raghavendra Busch, Christoph |
| contents | Face image quality assessment (FIQA) algorithms are being integrated into online identity management applications. These applications allow users to upload a face image as part of their document issuance process, where the image is then run through a quality assessment process to make sure it meets the quality and compliance requirements. Concerns about demographic bias have been raised about biometric systems, given the societal implications this may cause. It is therefore important that demographic variability in FIQA algorithms is assessed such that mitigation measures can be created. In this work, we study the demographic variability of all face image quality measures included in the ISO/IEC 29794-5 international standard across three demographic variables: age, gender, and skin tone. The results are rather promising and show no clear bias toward any specific demographic group for most measures. Only two quality measures are found to have considerable variations in their outcomes for different groups on the skin tone variable. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_07898 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Demographic Variability in Face Image Quality Measures Kabbani, Wassim Raja, Kiran Ramachandra, Raghavendra Busch, Christoph Computer Vision and Pattern Recognition Face image quality assessment (FIQA) algorithms are being integrated into online identity management applications. These applications allow users to upload a face image as part of their document issuance process, where the image is then run through a quality assessment process to make sure it meets the quality and compliance requirements. Concerns about demographic bias have been raised about biometric systems, given the societal implications this may cause. It is therefore important that demographic variability in FIQA algorithms is assessed such that mitigation measures can be created. In this work, we study the demographic variability of all face image quality measures included in the ISO/IEC 29794-5 international standard across three demographic variables: age, gender, and skin tone. The results are rather promising and show no clear bias toward any specific demographic group for most measures. Only two quality measures are found to have considerable variations in their outcomes for different groups on the skin tone variable. |
| title | Demographic Variability in Face Image Quality Measures |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2501.07898 |