A PPG-based biometric system using fuzzy min-max model

Yuze Zhang; Yaqi Zhang; Honghao Zhang

doi:10.1117/12.2660113

3 February 2023 A PPG-based biometric system using fuzzy min-max model

Yuze Zhang, Yaqi Zhang, Honghao Zhang

Proceedings Volume 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022); 1251111 (2023) https://doi.org/10.1117/12.2660113
Event: Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 2022, Hulun Buir, China

Abstract

Biometric methods have been widely used for privacy protection. Biometric recognition has unique and random characteristics, which can better protect people's privacy and security. In this paper, a biometric system based on plethysmography (PPG) signals using fuzzy min-max neural network are developed. The PPG signals have the ability of liveness detection compared with fingerprint recognition and face recognition. The system consists of three processes: signal preprocessing, feature extraction and model classification. The experimental results were obtained an accuracy of 97.62% in the Capnobase database.

Citation Download Citation

Yuze Zhang, Yaqi Zhang, and Honghao Zhang "A PPG-based biometric system using fuzzy min-max model", Proc. SPIE 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 1251111 (3 February 2023); https://doi.org/10.1117/12.2660113

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