Robust Multi biometric Recognition Using Face and Ear Images

TL;DR

This paper explores combining face and ear biometrics for authentication, demonstrating improved recognition accuracy through decision-level fusion on a new dataset.

Contribution

It introduces a novel approach of fusing face and ear biometrics at decision level, achieving higher recognition rates than using ear alone.

Findings

Ear biometric recognition rate of 90.7%

Fusion of face and ear improves recognition to 96%

Quality module reduces false rejections

Abstract

This study investigates the use of ear as a biometric for authentication and shows experimental results obtained on a newly created dataset of 420 images. Images are passed to a quality module in order to reduce False Rejection Rate. The Principal Component Analysis (eigen ear) approach was used, obtaining 90.7 percent recognition rate. Improvement in recognition results is obtained when ear biometric is fused with face biometric. The fusion is done at decision level, achieving a recognition rate of 96 percent.