This literature review surveyed research to date on the problem of using iris images acquired after death for automated human recognition
Post-mortem biometrics uses 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. In the current study, a comprehensive literature review was complemented by a summary of the most recent results and observations offered in these publications. This survey is unique in several elements. It is the first publication to consider iris recognition in which gallery images were acquired before death (peri-mortem images) and the probe images were acquired after death from the same subjects. The study is also unique in presenting results from the largest database of peri-mortem and post-mortem iris images, which were collected from 213 subjects by two independent institutions located in the United States and Poland. In addition, this study is unique in having assessed post-mortem recognition viability by using more than 20 iris recognition algorithms, ranging from the classic (e.g., Gabor filtering-based) to the modern (e.g., deep learning-based). Finally, the study is unique in providing a medically informed commentary on post-mortem iris, analyzing the reasons for recognition failures, and identifying key directions for future research. (publisher abstract modified)