z-logo
open-access-imgOpen Access
Robust Watermarking Using n-Diagonalization Based on Householder Transform
Author(s) -
Jaesung Park,
Kazuhito Sawase,
Hajime Nobuhara
Publication year - 2014
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2014.p0549
Subject(s) - digital watermarking , singular value decomposition , robustness (evolution) , computer science , watermark , discrete wavelet transform , singular value , wavelet , artificial intelligence , algorithm , transformation (genetics) , pattern recognition (psychology) , wavelet transform , computer vision , image (mathematics) , biochemistry , chemistry , eigenvalues and eigenvectors , physics , quantum mechanics , gene
Digital image watermarking based on singular value decomposition (SVD) is highly robust against misuse, but lacks the ability to distinguish whether watermarks are correct due to the importance of singular values being lower than two orthogonal matrices. To achieve highly accurate watermark extraction while maintaining high robustness, we propose robust watermarking based on discrete wavelet transform (DWT) and n -diagonalization formalized by Householder transformation. We propose that DWT be used to ensure visibility and that n -diagonalization be used to control information quantity related to watermark extraction accuracy. Experimental results confirm the robustness of our proposed method and that the extraction accuracy of the proposed method is approximately 2 times better than that of SVD.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom