Finger image quality assessment features - definitions and evaluation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F16%3APU136051" target="_blank" >RIV/00216305:26230/16:PU136051 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/7475528" target="_blank" >https://ieeexplore.ieee.org/document/7475528</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1049/iet-bmt.2014.0055" target="_blank" >10.1049/iet-bmt.2014.0055</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Finger image quality assessment features - definitions and evaluation

Popis výsledku v původním jazyce

Finger image quality assessment is a crucial part of any system where a high biometric performance and user satisfaction is desired. Several algorithms measuring selected aspects of finger image quality have been proposed in the literature, yet only few of them have found their way into quality assessment algorithms used in practice. The authors provide comprehensive algorithm descriptions and make available implementations of adaptations of ten quality assessment algorithms from the literature which operates at the local or the global image level. They evaluate the performance on four datasets in terms of the capability in determining samples causing false non-matches and by their Spearman correlation with sample utility. The authors' evaluation shows that both the capability in rejecting samples causing false non-matches and the correlation between features varies depending on the dataset.

Název v anglickém jazyce

Finger image quality assessment features - definitions and evaluation

Popis výsledku anglicky

Finger image quality assessment is a crucial part of any system where a high biometric performance and user satisfaction is desired. Several algorithms measuring selected aspects of finger image quality have been proposed in the literature, yet only few of them have found their way into quality assessment algorithms used in practice. The authors provide comprehensive algorithm descriptions and make available implementations of adaptations of ten quality assessment algorithms from the literature which operates at the local or the global image level. They evaluate the performance on four datasets in terms of the capability in determining samples causing false non-matches and by their Spearman correlation with sample utility. The authors' evaluation shows that both the capability in rejecting samples causing false non-matches and the correlation between features varies depending on the dataset.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LD14013" target="_blank" >LD14013: Nová řešení pro multimodální biometrii ? zvýšení bezpečnosti a spolehlivosti biometrických technologií</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IET Biometrics

ISSN

2047-4938

e-ISSN

2047-4946

Svazek periodika

5

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

18

Strana od-do

47-64

Kód UT WoS článku

000376976100002

EID výsledku v databázi Scopus

2-s2.0-84971441902