Are Gabor Kernels Optimal for Iris Recognition?

@article{Boyd2020AreGK,
  title={Are Gabor Kernels Optimal for Iris Recognition?},
  author={Aidan Boyd and Adam Czajka and K. Bowyer},
  journal={2020 IEEE International Joint Conference on Biometrics (IJCB)},
  year={2020},
  pages={1-9}
}
Gabor kernels are widely accepted as dominant filters for iris recognition. In this work we investigate, given the current interest in neural networks, if Gabor kernels are the only family of functions performing best in iris recognition, or if better filters can be learned directly from iris data. We use (on purpose) a single-layer convolutional neural network as it mimics an iris code-based algorithm. We learn two sets of data-driven kernels; one starting from randomly initialized weights and… Expand

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