Post Mortem Iris

Post-mortem iris recognition is an emerging forensic technique aiming to identify deceased individuals using their iris patterns, offering a supplementary method for human identification in challenging circumstances. Current research heavily utilizes deep learning, particularly convolutional neural networks (like ResNet, MobileNet, and DenseNet) and semantic segmentation models (SegNet, DeepLabV3+), to address the challenges posed by tissue decomposition in accurately segmenting and recognizing iris features. These advancements focus on improving accuracy and interpretability, with a particular emphasis on estimating the post-mortem interval from iris images. The successful development of robust and reliable post-mortem iris recognition systems could significantly enhance forensic investigations and improve the identification of deceased individuals.