Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48813
Title: Digital right management control for joint ownership of digital images using biometric features
Authors: Singh, Anushikha
Dutta, Malay Kishore
Travieso, Carlos M. 
Soni, K. M.
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
Keywords: Multiple biometric features
Iris Pattern Recognition
Robustness
Signal Processing Attacks
Digital watermarking
Perceptual Transparency
Issue Date: 2014
Journal: 2014 International Conference on Signal Processing and Integrated Networks, SPIN 2014
Conference: 1st International Conference on Signal Processing and Integrated Networks, SPIN 2014 
Abstract: This paper proposes a method to establish joint ownership of digital images by embedding imperceptible digital pattern in the image. This digital pattern is generated from biometric features of more than one subject in a strategic matter so that the identification of individual subject can be done and the multiple ownership of the digital images can be established. This digital pattern was embedded and extracted from the image and the experiments were also carried out when the image was subjected to signal processing attacks. Coefficients of mid frequency band discrete cosine transform was used for embedding as these coefficients do not adversely affect the perceptual transparency and is also significantly robust to normal signal processing attacks. Experimental results indicate that the insertion of this digital pattern does not change the perceptual properties of the image and the pattern survives signal processing attacks which can be extracted for unique identification. © 2014 IEEE.
URI: http://hdl.handle.net/10553/48813
ISBN: 9781479928668
Source: 2014 International Conference on Signal Processing and Integrated Networks, SPIN 2014 (6776941), p. 164-167
Appears in Collections:Actas de congresos
Show full item record

SCOPUSTM   
Citations

3
checked on Mar 7, 2021

Page view(s)

6
checked on Mar 8, 2021

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.