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DUTTA, M. K. SINGH, A. BURGET, R.
Originální název
Digital Ownership Tags Based on Biometric Features of Iris and Fingerprint for Content Protection and Ownership of Digital Images and Audio Signals
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
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.
Klíčová slova
Glaucoma, Fundus image, Optic Disc, Blood Vessels, Wavelet Transform, Feature Extraction, Classification
Autoři
DUTTA, M. K.; SINGH, A.; BURGET, R.
Rok RIV
2015
Vydáno
30. 9. 2015
Nakladatel
Multimedia Tools and Applications website, Springer Verlag
Místo
Nizozemsko
ISSN
1380-7501
Periodikum
MULTIMEDIA TOOLS AND APPLICATIONS
Ročník
79
Číslo
19
Stát
Strany od
20
Strany do
31
Strany počet
11
BibTex
@article{BUT115799, author="DUTTA, M. K. and SINGH, A. and BURGET, R.", title="Digital Ownership Tags Based on Biometric Features of Iris and Fingerprint for Content Protection and Ownership of Digital Images and Audio Signals", journal="MULTIMEDIA TOOLS AND APPLICATIONS", year="2015", volume="79", number="19", pages="20--31", doi="10.1007/s11042-015-2931-8", issn="1380-7501" }