Fingerprint Biometrics for Age Estimation: A Survey of Methods

Dr. Sumathy Kingslin and D. Dhivya
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Dr. Sumathy Kingslin: PG and Research Department of Computer Science Quaid-E-Millath Govt College for Women (A), Anna Salai, Chennai 600002, Tamilnadu, India
D. Dhivya: PG and Research Department of Computer Science Quaid-E-Millath Govt College for Women (A), Anna Salai, Chennai 600002, Tamilnadu, India

International Journal of Research and Scientific Innovation, 2025, vol. 12, issue 7, 1045-1055

Abstract: Estimating age from fingerprints is crucial in forensic science and biometrics due to the increasing use of fingerprints in various applications. This survey reviews existing age estimation methods based on fingerprints, including traditional approaches, machine learning-based methods, and deep learning techniques, highlighting their strengths, weaknesses, and limitations. Despite significant progress, there is still room for improvement in accuracy, robustness, and generalizability. Key challenges and future research directions are identified, providing a roadmap for advancing fingerprint-based age estimation. This survey serves as a valuable resource for researchers, practitioners, and forensic experts.

Date: 2025
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