Improving Rank-N Identification Rate of Palmprint Identification Using Permutation-Based Indexing

被引：0

作者：

Yoshihira, Mizuho ^{[1
]}

Serizawa, Ayumi ^{[1
]}

Okudera, Ryosuke ^{[1
]}

Ouchi, Yumo ^{[1
]}

Shiomi, Yuya ^{[1
]}

Nitta, Naoya ^{[2
]}

Nakahara, Masataka ^{[2
]}

Baba, Akira ^{[2
]}

Miyake, Yutaka ^{[2
]}

Ohki, Tetsushi ^{[1
]}

Nishigaki, Masakatsu ^{[1
]}

机构：

[1] Shizuoka Univ, Hamamatsu, Shizuoka, Japan

[2] KDDI Res Inc, Fijimino, Saitama, Japan

来源：

HCI FOR CYBERSECURITY, PRIVACY AND TRUST, HCI-CPT 2022 | 2022年 / 13333卷

关键词：

Biometric recognition; Palmprint identification; Permutation-based indexing;

D O I：

10.1007/978-3-031-05563-8_6

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Biometric information can have high similarity among different people but high variability within the same person. Therefore, it is difficult to identify a person or distinguish between two people based on biometric information. One way to address these issues is to use certain biometric information as pivots to define the feature space of biometric information. However, previous research has not sufficiently examined methods for selecting these pivots. In this study, schemes for pivot selection and robust palmprint identification are proposed that can improve the rank-N identification rate.

引用

页码：78 / 93

页数：16

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