Distinguishing Identical Twins in Biometric Systems: A Survey on Challenges and Advancements in Face Recognition

DOI

10.2991/978-94-6239-616-6_20How to use a DOI?

Keywords

Monozygotic Twins; Face Recognition; Biometric; Machine Learning; landmark detection

Abstract

Face recognition has achieved remarkable progress in recent years, yet the task of distinguishing monozygotic twins remains a major challenge due to their highly similar facial structures. Traditional biometric modalities, including 2D facial recognition and DNA-based identification, often fail to provide sufficient discriminative power, as identical twins share nearly identical genetic and morphological traits. This limitation poses critical security concerns in scenarios requiring high-accuracy identity verification. Recent studies have also shown that human capability to differentiate identical twins is limited, but humans may still perceive subtle discriminating traits that could inspire advanced algorithmic approaches. To address this problem, researchers are exploring Facial biometric technologies such as facial marks, micro-level facial features, and deep learning-based feature extraction. In particular, 3D facial recognition has emerged as a promising approach, offering robustness in unconstrained environments compared to conventional 2D systems. This survey provides an overview of current methodologies as 3D facial recognition, highlights the strengths and limitations of existing biometric systems in the context of identical twin recognition, and discusses future research directions for developing more reliable and discriminative multimodal biometric solutions.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - E. Valarmathi
AU  - G. Durga
AU  - C. Poojashree
AU  - M. Swathi
PY  - 2026
DA  - 2026/03/31
TI  - Distinguishing Identical Twins in Biometric Systems: A Survey on Challenges and Advancements in Face Recognition
BT  - Proceedings of the International Conference on Artificial Intelligence and Secure Data Analytics (ICAISDA 2025)
PB  - Atlantis Press
SP  - 238
EP  - 248
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-616-6_20
DO  - 10.2991/978-94-6239-616-6_20
ID  - Valarmathi2026
ER  -