Beyond Mortality: Advancements in Post-Mortem Iris Recognition through Data Collection and Computer-Aided Forensic Examination

arXiv cs.CV / 3/31/2026

💬 OpinionIdeas & Deep AnalysisTools & Practical UsageModels & Research

Key Points

  • The paper addresses both the promise and societal risks of post-mortem iris recognition, highlighting barriers such as the difficulty of collecting post-mortem iris datasets.
  • It introduces a new dataset containing NIR and visible-light iris images from 259 deceased subjects, with ISO/IEC 19794-6 compliance where possible and a maximum PMI of 1,674 hours.
  • It reports a rare longitudinal case where iris data was collected both before and after death for one subject, claimed as the first such published example.
  • The study evaluates state-of-the-art automatic forensic iris recognition using five methods across deceased-subject data (combined to reach 338 subjects) and analyzes effects of demographic factors on performance.
  • It contributes a post-mortem iris detection model (framing images as potential presentation attacks) and releases an open-source forensic tool that integrates multiple recognition methods with explainability for more interpretable comparisons.

Abstract

Post-mortem iris recognition brings both hope to the forensic community (a short-term but accurate and fast means of verifying identity) as well as concerns to society (its potential illicit use in post-mortem impersonation). These hopes and concerns have grown along with the volume of research in post-mortem iris recognition. Barriers to further progress in post-mortem iris recognition include the difficult nature of data collection, and the resulting small number of approaches designed specifically for comparing iris images of deceased subjects. This paper makes several unique contributions to mitigate these barriers. First, we have collected and we offer a new dataset of NIR (compliant with ISO/IEC 19794-6 where possible) and visible-light iris images collected after demise from 259 subjects, with the largest PMI (post-mortem interval) being 1,674 hours. For one subject, the data has been collected before and after death, the first such case ever published. Second, the collected dataset was combined with publicly-available post-mortem samples to assess the current state of the art in automatic forensic iris recognition with five iris recognition methods and data originating from 338 deceased subjects. These experiments include analyses of how selected demographic factors influence recognition performance. Thirdly, this study implements a model for detecting post-mortem iris images, which can be considered as presentation attacks. Finally, we offer an open-source forensic tool integrating three post-mortem iris recognition methods with explainability elements added to make the comparison process more human-interpretable.