By Topic

Singular value decomposition and wavelet-based iris biometric watermarking

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Majumder, S. ; Dept. of ECE, NERIST, Nirjuli, India ; Devi, K.J. ; Sarkar, S.K.

These days, with technological advancement, it is very easy for miscreants to produce illegal multimedia data copies. Various techniques of copyright protection of free data are being developed daily. Digital watermarking is one such technique, where digital embedding of the copyright information/watermark into the data to be protected. The two major ways of doing so are spatial domain and the robust transform domain. In this study, method for watermarking of digital images, with biometric data is presented. The usage of biometric instead of the traditional watermark increases the security of the image data. The biometric used here is iris. After the retinal scan, it is the most unique biometric. In terms of user friendliness in extracting the biometric, it comes after fingerprint and facial scan. The iris biometric template is generated from subject's eye images. The discrete cosine values of templates are extracted through discrete cosine transform and converted to binary code. This binary code is embedded in the singular values of the host image's coefficients generated through wavelet transform. The original image is thus firstly applied with the discrete wavelet transform followed up by the singular value decomposition of the subband coefficients. The algorithm has been tested with popular attacks for analysis of false recognition and rejection of subjects.

Published in:

Biometrics, IET  (Volume:2 ,  Issue: 1 )