Towards open-set touchless palmprint recognition via weight-based meta metric learning

Huikai Shao, Dexing Zhong

Abstract: Highlights•Weight-based Meta Metric Learning (W2ML) is proposed for open-set palmprint recognition.•Hard sample mining and weighting are adopted to improve the efficiency.•Extensive experiments are conducted on four constrained and unconstrained benchmarks.•By W2ML method, the identification accuracy is increased by up to 9.11%.•By W2ML method, Equal Error Rates (EER) is reduced by up to 2.97%.