Digital Ownership Tags Based on Biometric Features of Iris and Fingerprint for Content Protection and Ownership of Digital Images and Audio Signals

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F15%3APU115090" target="_blank" >RIV/00216305:26220/15:PU115090 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/s11042-015-2931-8" target="_blank" >http://dx.doi.org/10.1007/s11042-015-2931-8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11042-015-2931-8" target="_blank" >10.1007/s11042-015-2931-8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Digital Ownership Tags Based on Biometric Features of Iris and Fingerprint for Content Protection and Ownership of Digital Images and Audio Signals

Popis výsledku v původním jazyce

Abstract—Glaucoma is a disease of the retina which is one of the most common causes of permanent blindness worldwide. This paper presents an automatic image processing based method for glaucoma diagnosis from the digital fundus image. In this paper wavelet feature extraction has been followed by optimized genetic feature selection combined with several learning algorithms and various parameter settings. Unlike the existing research works where the features are considered from the complete fundus or a sub image of the fundus, this work is based on feature extraction from the segmented and blood vessel removed optic disc to improve the accuracy of identification. The experimental results presented in this paper indicate that the wavelet features of the segmented optic disc image are clinically more significant in comparison to features of the whole or sub fundus image in the detection of glaucoma from fundus image. Accuracy of glaucoma identification achieved in this work is 94.7 % and a comparison with existing methods of glaucoma detection from fundus image indicates that the proposed approach has improved accuracy of classification.

Název v anglickém jazyce

Digital Ownership Tags Based on Biometric Features of Iris and Fingerprint for Content Protection and Ownership of Digital Images and Audio Signals

Popis výsledku anglicky

Abstract—Glaucoma is a disease of the retina which is one of the most common causes of permanent blindness worldwide. This paper presents an automatic image processing based method for glaucoma diagnosis from the digital fundus image. In this paper wavelet feature extraction has been followed by optimized genetic feature selection combined with several learning algorithms and various parameter settings. Unlike the existing research works where the features are considered from the complete fundus or a sub image of the fundus, this work is based on feature extraction from the segmented and blood vessel removed optic disc to improve the accuracy of identification. The experimental results presented in this paper indicate that the wavelet features of the segmented optic disc image are clinically more significant in comparison to features of the whole or sub fundus image in the detection of glaucoma from fundus image. Accuracy of glaucoma identification achieved in this work is 94.7 % and a comparison with existing methods of glaucoma detection from fundus image indicates that the proposed approach has improved accuracy of classification.

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/LO1401" target="_blank" >LO1401: Interdisciplinární výzkum bezdrátových technologií</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

MULTIMEDIA TOOLS AND APPLICATIONS

ISSN

1380-7501

e-ISSN

1573-7721

Svazek periodika

79

Číslo periodika v rámci svazku

19

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

11

Strana od-do

20-31

Kód UT WoS článku

000388121700063

EID výsledku v databázi Scopus

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