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A Robust and Oblivious Watermarking Method Using Maximum Wavelet Coefficient Modulation and Genetic Algorithm

In: Modeling and Simulation in Engineering - Selected Problems

Author

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  • Surya Prasada Rao Borra
  • Kongara Ramanjaneyulu
  • K Raja Rajeswari

Abstract

An image watermarking method using Discrete Wavelet Transform (DWT) and Genetic Algorithm (GA) is presented for applications like content authentication and copyright protection. This method is robust to various image attacks. For watermark detection/extraction, the cover image is not essential. Gray scale images of size 512 × 512 as cover image and binary images of size 64 × 64 as watermark are used in the simulation of the proposed method. Watermark embedding is done in the DWT domain. 3rd and 2nd level detail sub-band coefficients are selected for further processing. Selected coefficients are arranged in different blocks. The size of the block and the number blocks depends on the size of the watermark. One watermark bit is embedded in each block. Then, inverse DWT operation is performed to get the required watermarked image. This watermarked image is used for transmission and distribution purposes. In case of any dispute over the ownership, the hidden watermark is decoded to solve the problem. Threshold-based method is used for watermark extraction. Control parameters are identified and optimized based on GA for targeted performance in terms of PSNR and NCC. Performance comparison is done with the existing works and substantial improvement is witnessed.

Suggested Citation

  • Surya Prasada Rao Borra & Kongara Ramanjaneyulu & K Raja Rajeswari, 2020. "A Robust and Oblivious Watermarking Method Using Maximum Wavelet Coefficient Modulation and Genetic Algorithm," Chapters, in: Jan Valdman & Leszek Marcinkowski (ed.), Modeling and Simulation in Engineering - Selected Problems, IntechOpen.
    • Handle: RePEc:ito:pchaps:213543
    DOI: 10.5772/intechopen.93832
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    More about this item

    Keywords

    image watermarking; discrete wavelet transform; genetic algorithm; PSNR and NCC;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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