Post-Mortem Iris Recognition—A Survey and Assessment of the State of the Art

Abstract

Post-mortem biometrics entails utilizing the biometric data of a deceased individual for determining or verifying human identity. Due to fundamental biological changes that occur in a person's biometric traits after death, post-mortem data can be significantly different from ante-mortem data, introducing new challenges for biometric sensors, feature extractors and matchers. This paper surveys research to date on the problem of using iris images acquired after death for automated human recognition. A comprehensive review of existing literature is complemented by a summary of the most recent results and observations offered in these publications. This survey is unique in several elements. Firstly, it is the first publication to consider iris recognition where gallery images are acquired before death (perimortem images) and the probe images are acquired after death from the same subjects. Secondly, results are presented from the largest database of peri-mortem and post-mortem iris images, collected from 213 subjects by two independent institutions located in the U.S. and Poland. Thirdly, post-mortem recognition viability is assessed using more than 20 iris recognition algorithms, ranging from the classic (e.g., Gabor filteringbased) to the modern (e.g., deep learning-based). Finally, we provide a medically informed commentary on post-mortem iris, analyze the reasons for recognition failures, and identify key directions for future research.

Automatic Face Recognition for Forensic Identification of Persons Deceased in Humanitarian Emergencies

“…However, fingerprint recognition methods cannot be applied in a wide number of cases because of the unavailability of antemortem samples or because the finger skin of the deceased is degraded. Some studies evaluated the feasibility of postmortem iris recognition [8], revealing that the this biometric trait degrades in less than one week, even if the body is conserved in controlled environmental conditions.…”

Interpretable Deep Learning-Based Forensic Iris Segmentation and Recognition

“…These studies suggest that (a) postmortem iris recognition is possible, and (b) its performance highly depends on ambient conditions. Boyd et al [11] summarized multiple facets of postmortem iris recognition in a comprehensive survey.…”

Chaotic Krill Herd with Deep Transfer Learning-Based Biometric Iris Recognition System

“…Security sciences have started leveraging interesting elements for the past few years to ensure secure admission to confined places since it has become a crucial issue. The rising interest upon effective security confirmation frameworks has boosted the development of verification frameworks that are safer and highly proficient [1,2]. Conventional ways to deal with Iris Detection (ID), for example, utilization of a key or secret phrase is unacceptable in selected applications.…”