Publication detail

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

DUTTA, M. K. SINGH, A. BURGET, R.

Original Title

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

Type

journal article in Web of Science

Language

English

Original Abstract

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.

Keywords

Glaucoma, Fundus image, Optic Disc, Blood Vessels, Wavelet Transform, Feature Extraction, Classification

Authors

DUTTA, M. K.; SINGH, A.; BURGET, R.

RIV year

2015

Released

30. 9. 2015

Publisher

Multimedia Tools and Applications website, Springer Verlag

Location

Nizozemsko

ISBN

1380-7501

Periodical

MULTIMEDIA TOOLS AND APPLICATIONS

Year of study

79

Number

19

State

Kingdom of the Netherlands

Pages from

20

Pages to

31

Pages count

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"
}