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Domain-Specific Human-Inspired Binarized Statistical Image Features for Iris Recognition
Iris image patches used in training and source codes of the method proposed in: Adam Czajka, Daniel Moreira, Kevin W. Bowyer, Patrick J. Flynn, "Domain-Specific Human-Inspired Binarized Statistical Image Features for Iris Recognition," WACV 2019, Hawaii, 2019 Pre-print available at: https://arxiv.org/abs/1807.05248 Please follow the instructions at https://cvrl.nd.edu/projects/data/ to get copies of these sets. WACV_2019_Czajka_etal_Stest_GENUINE.csv and WACV_2019_Czajka_etal_Stest_IMPOSTOR.csv files define genuine and impostor matching pairs used to generate Fig. 12 in the paper. UsageThe example code example.m shows how to use the re-trained BSIF filters in iris recognition. |
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