Post-Mortem Iris Recognition Resistant to Biological Eye Decay Processes

Mateusz Trokielewicz, Adam Czajka, Piotr Maciejewicz; Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2020, pp. 2307-2315

Abstract


This paper proposes an end-to-end iris recognition method designed specifically for post-mortem samples, and thus serving as a perfect application for iris biometrics in forensics. To our knowledge, it is the first method specific for verification of iris samples acquired after demise. We have fine-tuned a convolutional neural network-based segmentation model with a large set of diversified iris data (including post-mortem and diseased eyes), and combined Gabor kernels with newly designed, iris-specific kernels learnt by Siamese networks. The resulting method significantly outperforms the existing off-the-shelf iris recognition methods (both academic and commercial) on the newly collected database of post-mortem iris images and for all available time horizons since death. We make all models and the method itself available along with this paper.

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[bibtex]
@InProceedings{Trokielewicz_2020_WACV,
author = {Trokielewicz, Mateusz and Czajka, Adam and Maciejewicz, Piotr},
title = {Post-Mortem Iris Recognition Resistant to Biological Eye Decay Processes},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {March},
year = {2020}
}