Multimodal Personal Ear Authentication Using Smartphones
This work addresses authentication issues for smartphone users when traditional methods like fingerprint or face recognition are unreliable, though it appears incremental by combining existing modalities.
The paper tackles the problem of biometric authentication on smartphones by proposing a multimodal system using the pinna's acoustic transfer function (PRTF), pinna images, and positional sensor data to compensate for measurement positional fluctuations, resulting in improved robustness.
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.