Publications

@article{apap_explainable_2024,

title = {Explainable multi-layer COSFIRE filters robust to corruptions and boundary attack with application to retina and palmprint biometrics},

author = {Adrian Apap and Amey Bhole and Laura Fernández-Robles and Manuel Castejón-Limas and George Azzopardi},

url = {https://link.springer.com/article/10.1007/s00521-024-10164-8},

year  = {2024},

date = {2024-01-01},

journal = {Neural Computing and Applications},

volume = {36},

number = {30},

pages = {19231–19245},

abstract = {This work introduces a unified and explainable biometric recognition method using hierarchical COSFIRE filters for retina and palmprint identification. The approach leverages COSFIRE’s one-shot trainable nature to capture spatial arrangements of keypoints in biometric images. It delivers state-of-the-art accuracy, including perfect classification on retina datasets and 97.54% on a palmprint dataset. The system remains robust against partial data and most adversarial attacks, while also offering clear, interpretable decision processes suitable for broader applications.},

note = {Publisher: Springer London London},

keywords = {biometrics, COSFIRE Filters, Explanaible AI},

pubstate = {published},

tppubtype = {article}

}