Colour Image Watermarking Scheme Using Hidden Markov Model



This is an IEEE paper for ME/MTech Student, Need to develop this IEEE paper for Color Images. Kindly check the attachment and then only bid.

Achieving robustness, imperceptibility and high capacity simultaneously is of great importance in digital watermarking. This paper presents a new informed image watermarking scheme with high robustness and simplified complexity at an information rate of 1/64 bit/pixel. Firstly, a Taylor series

approximated locally optimum test (TLOT) detector based on the hidden Markov model (HMM) in the wavelet domain is developed to tackle the problem of unavailability of exact embedding strength in the receiver due to informed embedding. Then based on the TLOT detector and the concept of dirty-paper code design, new HMM-based spherical codes are constructed to provide an effective tradeoff between robustness and distortion. The process of informed embedding is formulated as an optimization problem under the robustness and distortion constraints and the genetic algorithm (GA) is then employed to solve this problem. Moreover, the perceptual distance in the wavelet domain is also developed and incorporated into the GA-based optimization. Simulation results demonstrate that the proposed informed watermarking algorithm has high robustness against common attacks in signal processing and shows a comparable performance to the state-of-the-art scheme with a greatly reduced arithmetic complexity.

Skills: Algorithm, Mathematics, Matlab and Mathematica

See more: test algorithm, taylor design, problem algorithm, importance of algorithm, digital domain, develop an algorithm, develop algorithm, complexity of an algorithm, complexity of algorithm, algorithm test, algorithm problem, algorithm complexity, algorithm and complexity, simulation in matlab, signal matlab, scheme, optimization model, optimization algorithm, new matlab, matlab test, matlab signal processing, matlab problem, matlab image, mathematica signal processing, image optimization matlab

Project ID: #4984932

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