1.

Record Nr.

UNINA9911015866603321

Autore

Zhang David

Titolo

Advanced Palmprint Authentication / / by David Zhang, Dandan Fan, Xu Liang, Bob Zhang

Pubbl/distr/stampa

Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025

ISBN

981-9671-01-9

Edizione

[1st ed. 2025.]

Descrizione fisica

1 online resource (506 pages)

Altri autori (Persone)

FanDandan

LiangXu

ZhangBob

Disciplina

006.248

Soggetti

Biometric identification

Computer vision

Pattern recognition systems

Machine learning

Biometrics

Computer Vision

Automated Pattern Recognition

Machine Learning

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Chapter 1 Towards Next-Generation Palmprint Recognition -- Part I CONTACT-BASED PALMPRINT RECOGNITION -- Chapter 2 Jointly Heterogeneous Palmprint Discriminant Feature Learning -- Chapter 3 Rich Orientation Coding for Large-Scale Palmprint Image Analysis -- Chapter 4 Hybrid Fusion Combining Palmprint and Palm Vein for Large-scale Palm-based Recognition -- Part II CONTACTLESS PALMPRINT RECOGNITION -- Chapter 5 Keypoint Localization Neural Network for Touchless Palmprint Recognition Based on Edge-Aware Regression -- Chapter 6 Hand-Geometry Aware Image Quality Assessment Framework for Contactless Palmprint Recognition -- Chapter 7 Touchless Palmprint Recognition Based on 3D Gabor Template and Block Feature Refinement -- Chapter 8 Aligned Multilevel Gabor Convolution Network for Palmprint Recognition -- Chapter 9 Contactless Palmprint



Recognition System based on Dual-camera Alignment -- Part III MULTIPLE PALMPRINT SENSING SYSTEMS -- Chapter 10 Multi-camera System for High Speed Touchless Palm Recognition -- Chapter 11 Line-Scan Palmprint Acquisition System -- Chapter 12 Person Recognition Using 3-D Palmprint Data Based on Full-Field Sinusoidal FringeProjection -- Chapter 13 Complete Binary Representation for 3-D Palmprint Recognition -- Chapter 14 Book Reivew and Future Work.

Sommario/riassunto

This book presents a comprehensive exploration of palmprint recognition, synthesizing over a decade of research in contact-based, contactless, 3D, and multispectral systems. As one of the earliest approaches in biometrics, contact-based palmprint systems have evolved significantly, achieving greater portability and accuracy, even when handling large-scale datasets. In contrast, contactless systems, which allow users to position their palms near the camera without physical contact, offer a hygienic, user-friendly alternative that has quickly gained popularity in various applications. Additionally, the advancement of 3D palmprint recognition and the introduction of cutting-edge sensors, such as line-scan and multicamera systems, have further enhanced the accuracy and reliability of these systems. This book is structured into 13 chapters, divided into three key sections. The first part delves into contact-based systems, emphasizing their growing efficiency and performance in both small devices and large-scale scenarios. The second part provides in-depth coverage of contactless systems, detailing essential processes like palmprint acquisition, ROI localization, feature extraction, and matching techniques. The third section examines the latest developments in multiple sensing systems, focusing on 3D and multispectral recognition. Targeted at researchers and engineers in biometrics, particularly those specializing in palmprint recognition, this book offers valuable insights and practical algorithms for enhancing system performance. It is also an excellent resource for readers with a broader interest in biometric technologies, offering a rich understanding of the latest trends and innovations in the field.