.png){kind=icon}
返回
RHEMAT: Robust human ear based multimodal authentication technique
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cose.2023.103356.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Ear biometrics is a fast-developing field of computer vision that offers several advantages over existing biometric authentication methods. The performance of the ear is superior to or comparable to that of other biometric traits. However, the recognition performance of 2D ear images degrades due to the impacts of posture, illumination, and scaling. To overcome these challenges, we propose combining 3D and 2D ear images and constructing a keypoint detector and descriptor using a covariance matrix derived from texture and geometry information. The feature vector of the descriptor is then used to describe keypoints and utilized to identify keypoints with the smallest distance between a probe and gallery for the subsequent registration process. The registration error that results serves as the matching score. The proposed method is evaluated on a large database of ear images and compared to state-of-the-art techniques, demonstrating superior performance in occlusion, noise, and pose variations. & COPY; 2023 Published by Elsevier Ltd.
Keyword:
3D Ear
Authentication
Multimodal
Security
Biometrics
期刊
C
IF:
5.4
论文数:
4.6K
被引数:
1.4W
机构
引用论文
分享收藏分享收藏Reversing the irreversible: A survey on inverse biometrics逆转不可逆: 逆向生物识别研究综述.png)
COMPUTERS & SECURITY
OAAI
COMPUTERS & SECURITYIF5.4
OAAI分享收藏Evaluating multi-modal mobile behavioral biometrics using public datasetsCOMPUTERS & SECURITY
COMPUTERS & SECURITYIF5.4
PREAI
分享收藏分享收藏
查看更多内容