Biometric Systems

doi:10.3390/books978-3-0365-1129-0

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Biometric Systems

Edited by

August 2021

352 pages

ISBN978-3-0365-1128-3 (Hardback)
ISBN978-3-0365-1129-0 (PDF)

https://doi.org/10.3390/books978-3-0365-1129-0

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This book is a reprint of the Special Issue Biometric Systems that was published in

Chemistry & Materials Science

Engineering

Environmental & Earth Sciences

Summary

Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study.

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Keywords

online signature verification; shape contexts; function features; SC-DTW; symbolic representation; two-stage method; finger features; multimodal recognition; local coding; Gabor filter; LGS; human identification; biomarker; ECG; machine learning; Physionet; Lviv Biometric Dataset; biometry; identification; bloodstream; image recognition; multi-biometrics; bit planes; block; mutual information; cross-device; dorsal hand vein recognition; person re-identification; superpixel; temporally aligned pooling; walking cycle; automatic recognition; face; voice; body motion; autism spectrum disorder (ASD); assessment; intervention; curve similarity; curve similarity model; curve similarity transformation; similarity distance; segmentation matching; evolutionary computation; finger vein recognition; hand vein recognition; contactless acquisition device; public vascular pattern dataset; biometric recognition performance evaluation; face verification; optical correlation; Hausdorff distance; image classification; face detection; depth map ensemble; filtering; geometric deep learning; ear detection; structured prediction; semantic segmentation; rotation equivariance; Gaussian mixture model; superpixels; face recognition systems; person identification; biometric systems; survey; automatic signature verification; touch-screen sensor; data quality; enrollment phase; performance assessment; augmented signature; security enhancement; mobile conditions; biometric recognition; visible light iris images; image quality assessment; image covariates; quality filtering; vascular biometric recognition; wrist vein recognition; contactless dataset; identification; pattern recognition; infrared camera; non-contact devices; Scale-Invariant Feature Transform (SIFT^®); Speeded Up Robust Features (SURF^®); Oriented FAST and Rotated BRIEF (ORB); fingerprint; ECG; presentation attack detection; deep learning