Quality Measures in Biometric Systems
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Abstract (arXiv)
Biometric technology has been increasingly deployed in the past decade, offering greater security and convenience than traditional methods of personal recognition. Although biometric signals' quality heavily affects a biometric system's performance, prior research on evaluating quality is limited. Quality is a critical issue in security, especially in adverse scenarios involving surveillance cameras, forensics, portable devices, or remote access through the Internet. This article analyzes what factors negatively impact biometric quality, how to overcome them, and how to incorporate quality measures into biometric systems. A review of the state of the art in these matters gives an overall framework for the challenges of biometric quality.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 1 of its 34 references that are in the map. First posted on arXiv 17 Nov 2021.
Builds on
1 of 34 references.
References · 1
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Citing papers per year: 2022: 6; 2023: 2; 2024: 0; 2025: 2; 2026: 2.
12 papers.
- 2022Deep Learning for Iris Recognition: A Surveycited by 25
- 2022Handwriting Biometrics: Applications and Future Trends in e-Security and e-Healthcited by 19
- 2022Facial Soft Biometrics for Recognition in the Wild: Recent Works, Annotation, and COTS Evaluationcited by 19
- 2023Toward Face Biometric De-identification using Adversarial Examplescited by 8
- 2022FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessmentcited by 4
- 2023An Explainable Model-Agnostic Algorithm for CNN-based Biometrics Verificationcited by 4
- 2025Comparison of Visual Trackers for Biomechanical Analysis of Runningcited by 2
- 2025Ocular Authentication: Fusion of Gaze and Periocular Modalitiescited by 2
- 2022A Survey of Super-Resolution in Iris Biometrics with Evaluation of Dictionary-Learningcited by 1
- 2022Forensicability Assessment of Questioned Images in Recapturing Detectioncited by 0
- 2026Beyond Error-vs-Discard Characteristic: Toward Stable and Reliable Evaluation for Face Image Quality Assessmentcited by 0
- 2026Mobile Interaction for Assessing Fatigue, Sleep, and Activity in Neurodegenerative and Chronic Diseasescited by 0
- 2026Beyond Error-vs-Discard Characteristic: Toward Stable and Reliable Evaluation for Face Image Quality Assessment23 Jul 2026
- 2026Mobile Interaction for Assessing Fatigue, Sleep, and Activity in Neurodegenerative and Chronic Diseases9 Jun 2026
- 2025Ocular Authentication: Fusion of Gaze and Periocular Modalities22 May 2025
- 2025Comparison of Visual Trackers for Biomechanical Analysis of Running7 May 2025
- 2023An Explainable Model-Agnostic Algorithm for CNN-based Biometrics Verification25 Jul 2023
- 2023Toward Face Biometric De-identification using Adversarial Examples7 Feb 2023
- 2022Facial Soft Biometrics for Recognition in the Wild: Recent Works, Annotation, and COTS Evaluation24 Oct 2022
- 2022Deep Learning for Iris Recognition: A Survey12 Oct 2022
- 2022Forensicability Assessment of Questioned Images in Recapturing Detection5 Sep 2022
- 2022A Survey of Super-Resolution in Iris Biometrics with Evaluation of Dictionary-Learning27 Mar 2022
- 2022Handwriting Biometrics: Applications and Future Trends in e-Security and e-Health24 Feb 2022
- 2022FaceQgen: Semi-Supervised Deep Learning for Face Image Quality Assessment3 Jan 2022