Multimodal Personal Ear Authentication Using Smartphones

TL;DR

This paper proposes a multimodal biometric authentication system for smartphones that combines acoustic transfer function of the pinna, pinna images, and positional data to improve robustness and accuracy over previous methods.

Contribution

It introduces a novel multimodal approach integrating PRTF, images, and sensor data to enhance biometric authentication robustness on smartphones.

Findings

The system compensates for positional fluctuations in measurements.

Multimodal approach improves authentication accuracy and robustness.

Effective in scenarios where traditional biometrics fail.

Abstract

In recent years, biometric authentication technology for smartphones has become widespread, with the mainstream methods being fingerprint authentication and face recognition. However, fingerprint authentication cannot be used when hands are wet, and face recognition cannot be used when a person is wearing a mask. Therefore, we examine a personal authentication system using the pinna as a new approach for biometric authentication on smartphones. Authentication systems based on the acoustic transfer function of the pinna (PRTF: Pinna Related Transfer Function) have been investigated. However, the authentication accuracy decreases due to the positional fluctuation across each measurement. In this paper, we propose multimodal personal authentication on smartphones using PRTF. The pinna image and positional sensor information are used with the PRTF, and the effectiveness of the authentication method is examined. We demonstrate that the proposed authentication system can compensate for the positional changes in each measurement and improve robustness.