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Robust image data hiding using geometric mean quantization

Akhaee, M. A ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/GLOCOM.2009.5426109
  3. Abstract:
  4. In this paper, a novel quantization based watermarking method is proposed. For blind detection, a set of nonlinear convex functions based on geometric mean are investigated. In order to achieve minimum distortion, the optimum function set is found. The algorithm is implemented on the approximation coefficients of wavelet transform for natural images. In order to make the algorithm more robust and imperceptible, a new transform domain called Point to Point Graph (PPG), which converts a 1-D signal to a 2-D one, has been used. The error probability of the proposed scheme is analytically investigated. Simulation results show that this algorithm has great robustness against common attacks such as AWGN, JPEG and rotation in comparison with recent methods presented so far
  5. Keywords:
  6. Geometric quantization ; Image watermarking ; Minimum distortion ; Approximation coefficients ; Blind detection ; Convex functions ; Error probabilities ; Function sets ; Geometric mean ; Image data hiding ; Natural images ; Point to point ; Quantization-based watermarking ; Simulation result ; Transform domain ; Approximation algorithms ; Computational fluid dynamics ; Probability ; Quantum theory ; Watermarking ; Wavelet transforms ; Geometry
  7. Source: GLOBECOM - IEEE Global Telecommunications Conference, 30 November 2009 through 4 December 2009, Honolulu, HI ; 2009 ; 9781424441488 (ISBN)
  8. URL: http://ieeexplore.ieee.org/document/5426109