IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Touchless Palmprint Recognition and Its Evaluation on a Large-Scale Dataset

Touchless Palmprint Recognition and Its Evaluation on a Large-Scale Dataset
View Sample PDF
Author(s): Xu Liang (The Chinese University of Hong Kong, Shenzhen, China), Chunsheng Zhang (The Chinese University of Hong Kong, Shenzhen, China), Wei Jia (Hefei University of Technology, China)and David Zhang (The Chinese University of Hong Kong, Shenzhen, China)
Copyright: 2025
Pages: 18
Source title: Encyclopedia of Information Science and Technology, Sixth Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Founding Editor-in-Chief, Information Resources Management Journal (IRMJ), USA)
DOI: 10.4018/978-1-6684-7366-5.ch047

Purchase

View Touchless Palmprint Recognition and Its Evaluation on a Large-Scale Dataset on the publisher's website for pricing and purchasing information.

Abstract

Palmprint recognition is a technology that uses the unique composite texture information of the palm surface for automatic identification. In this chapter, first, the main research contents of touchless palmprint recognition are introduced. Second, the establishment of the CUHKSZ large-scale touchless palmprint dataset will be described in detail. Third, parameter optimization experiments are conducted on the CUHKSZ dataset to observe the scientific problems caused by the increase in data scale. Fourth, the experiment comparing the EER of the most used touchless palmprint recognition algorithms on the large-scale dataset will be performed to provide baselines for future research. Finally, the recognition performances of the three most widely used biometric modals, including palmprint, face, and fingerprint, will be compared on the CUHKSZ dataset, which can demonstrate the advantages of touchless palmprint recognition. In the end of this chapter, future research directions will be put forward.

Related Content

Christian Rainero, Giuseppe Modarelli. © 2025. 26 pages.
Beatriz Maria Simões Ramos da Silva, Vicente Aguilar Nepomuceno de Oliveira, Jorge Magalhães. © 2025. 21 pages.
Ann Armstrong, Albert J. Gale. © 2025. 19 pages.
Zhi Quan, Yueyi Zhang. © 2025. 21 pages.
Sanaz Adibian. © 2025. 19 pages.
Le Ngoc Quang, Kulthida Tuamsuk. © 2025. 21 pages.
Jorge Lima de Magalhães, Carla Cristina de Freitas da Silveira, Tatiana Aragão Figueiredo, Felipe Gilio Guzzo. © 2025. 17 pages.
Body Bottom