Human iris, with its highly complex, stable, and unique patterns, has gained increasing attention as a reliable biometric modality. In forensic ophthalmology, iris recognition presents significant promise for secure identification of suspects, victims, and missing persons, as well as in disaster victim identification (DVI). Unlike fingerprints or DNA, which may be degraded or unavailable, iris-based methods provide a non-invasive and highly accurate alternative with strong potential for forensic application.

Technological progress has accelerated this field, particularly with the introduction of artificial intelligence and deep learning–based algorithms. These approaches demonstrate resilience against common forensic challenges such as off-angle images, partial occlusions, and poor lighting. Multimodal biometric systems—integrating iris data with retina, sclera, or periocular features—offer further robustness. Advanced imaging modalities such as Optical Coherence Tomography Angiography (OCTA) not only strengthen anti-spoofing measures but also enable exploration of health-related biomarkers, including diabetic risk prediction, thereby expanding medico-legal applications.

Despite its promise, critical limitations persist. The post-mortem usability of the iris remains confined to a short time window, while lack of standardized collection protocols, forensic-specific validation studies, and precedent-setting case law impede broader acceptance. Ethical and legal concerns—ranging from privacy and consent to admissibility under Daubert and Frye standards—further complicate its forensic deployment.

Future directions demand interdisciplinary collaboration to establish standard operating procedures, validation frameworks, and ethical safeguards. By addressing these challenges, iris biometrics can evolve from a supportive tool to a scientifically validated, court-admissible pillar of forensic identification.

Iris biometrics, Forensic, Post-mortem identification, Artificial intelligence