异质虹膜识别研究综述

doi:10.11896/jsjkx.231200175

Abstract

Abstract: The variations in iris image acquisition environment and devices result in significant disparities in iris registration and recognition samples,which brings challenges to the traditional iris recognition technology.Heterogeneous iris recognition has emerged as a focal point of interest in both academic and industrial domains.This paper classifies and summarizes the existing he-terogeneous iris recognition methods from three perspectives:different levels,sample distinctiveness,and single-source versus multi-source scenarios,and summarizes the latest advancements in heterogeneous iris recognition.Existing heterogeneous iris datasets are reviewed according to the classification of cross-quality,cross-device and cross-spectrum,and the iris recognition evaluation metrics are summarized so that researchers can better evaluate and validate the algorithm performance.Finally,the future development direction of heterogeneous iris recognition is prospected,focusing on three aspects:environmental robustness,modeling of data heterogeneity and multimodal fusion.

Key words: Iris recognition, Heterogeneous images, Biometrics, Deep learning

CLC Number:

TP391.41

KONG Jialin, ZHANG Qi, WANG Caiyong. Review of Heterogeneous Iris Recognition[J].Computer Science, 2024, 51(6): 186-197.

References

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