Research article Special Issues

Robust digital watermarking for color images in combined DFT and DT-CWT domains

  • Received: 08 February 2019 Accepted: 24 April 2019 Published: 04 June 2019
  • Image watermarking focuses on hiding secret data into the cover image imperceptibly to protect the copyright of the original image. In this paper, we propose a new framework of robust digital watermarking for color images using combined embedding techniques of Discrete Fourier Transform (DFT) and Dual Tree Complex Wavelet Transform (DTCWT). The cover image is first divided into Y, U and V channels. The Y channel is then transformed by DFT and partitioned into the ring shapes. With an embedding key, we generate pseudo-random patterns to represent the watermark. These patterns are also transformed and partitioned. The watermark represented by the selection of patterns is then embedded into the rings of the DFT coefficients. We further embed a rectification watermark into the U channel, in which DTCWT is applied to achieve a capability of geometric distortion resilience. On the recipient's side, the detection and extraction of watermark can be successfully done. Compared with previous schemes, the proposed method is better on preserving the image quality. Meanwhile, the robustness against typical attacks is also stronger.

    Citation: Qichao Ying, Jingzhi Lin, Zhenxing Qian, Haisheng Xu, Xinpeng Zhang. Robust digital watermarking for color images in combined DFT and DT-CWT domains[J]. Mathematical Biosciences and Engineering, 2019, 16(5): 4788-4801. doi: 10.3934/mbe.2019241

    Related Papers:

  • Image watermarking focuses on hiding secret data into the cover image imperceptibly to protect the copyright of the original image. In this paper, we propose a new framework of robust digital watermarking for color images using combined embedding techniques of Discrete Fourier Transform (DFT) and Dual Tree Complex Wavelet Transform (DTCWT). The cover image is first divided into Y, U and V channels. The Y channel is then transformed by DFT and partitioned into the ring shapes. With an embedding key, we generate pseudo-random patterns to represent the watermark. These patterns are also transformed and partitioned. The watermark represented by the selection of patterns is then embedded into the rings of the DFT coefficients. We further embed a rectification watermark into the U channel, in which DTCWT is applied to achieve a capability of geometric distortion resilience. On the recipient's side, the detection and extraction of watermark can be successfully done. Compared with previous schemes, the proposed method is better on preserving the image quality. Meanwhile, the robustness against typical attacks is also stronger.


    加载中


    [1] H. Larijani and G. Rad, A new spatial domain algorithm for gray scale images watermarking, International Conference on Computer and Communication Engineering, (2008), 157–161.
    [2] H. Nemade and V. Kelkar, Reversible watermarking for colored medical images using histogram shifting method, 3rd International Conference on Computing for Sustainable Global Development, (2016), 2664–2668.
    [3] A. Al-Nu'aimi and R. Qahwaji, Adaptive watermarking for digital colored images based on the energey of edges, IEEE International Conference on Signal Processing and Communications, (2007), 1371–1374.
    [4] J. O'Ruanaidh and T. Pun, Rotation, scale, and translation invariant digital image watermarking, Sign. Process., 66 (1998), 303–317.
    [5] F. N. Thakkar and V. K. Srivastava, A blind medical image watermarking: DWT-SVD based robust and secure approach for telemedicine applications. Multimed. Tools Appl., 76 (2017), 3669–3697.
    [6] H. Hu and H. Lyu, Collective blind image watermarking in DWT-DCT domain with adaptive embedding strength governed by quality metrics, Multimed. Tools Appl., 76 (2017), 6575–6594.
    [7] S. Horng, A blind image copyright protection scheme for e-government. J. Vis. Communic. Image, 24 (2013), 1099–1105.
    [8] S. A. Parah, J. A. Sheikh, N. A. Loan, et al., Robust and blind watermarking technique in DCT domain using inter-block coefficient differencing, Dig. Signal Process., 53 (2016), 11–24.
    [9] X. Kang, J. Huang and W. Zeng, Efficient general print-scanning resilient data hiding based on uniform log-polar mapping, IEEE T. Inf. Foren. Sec., 5 (2010), 1–12.
    [10] D. Zheng, J. Zhao and A. El. Saddik, RST invariant digital image watermarking based on log-polar mapping and phase correlation, IEEE T. Circ. Syst. Vid., 13 (2003), 753–765.
    [11] P. Niu, X. Wang, H. Jin, et al., A feature-based robust digital image watermarking scheme using Bandelet transform, Optics Laser Tech., 43 (2011), 437–450.
    [12] M. Amini, M. O. Ahmad and M. N. S. Swamy, A robust multibit multiplicative watermark decoder using vector-based hidden Markov model in wavelet domain, IEEE T. Circ. Syst. Vid., 28 (2018), 402–413.
    [13] M. Amini, M. O. Ahmad and M. N. S. Swamy, Digital watermark extraction in wavelet domain using hidden Markov model, Multimed. Tools Appl., 76 (2017), 3731–3749.
    [14] E. Nezhadarya, Z. J. Wang and R. K. Ward, Robust image watermarking based on multiscale gradient direction quantization, IEEE T. Inf. Foren. Sec., 6 (2011), 1200–1213.
    [15] V Ananthaneni, U. R.Nelakuditi, Hybrid digital image watermarking using contourlet transform (CT), DCT and SVD. Int. J. Image Process., 11 (2017), 85–93.
    [16] A. K. Singh, M. Dave and A. Mohan, Hybrid technique for robust and imperceptible image watermarking in DWT–DCT–SVD Domain. Natl. Acad. Sci. Lett., 37 (2014) 351–358.
    [17] Z. Wang, A. C. Bovik, H. R. Sheik, et al., Image quality assessment: from error visibility to structural similarity, IEEE T. Image Process., 13 (2004), 600–612.
    [18] UCID-an Uncompressed Colour Image Database–a benchmark database for image retrieval with predefined ground truth, Accessed: 2019. (available: http://imagedatabase.cs.washington.edu/groundtruth/)
    [19] T. Lin, M. Maire, S. Belongie, et al., Microsoft COCO: Common objects in context, European Conference on Computer Vision, (2014), 740–755, Accessed: 2019. (available: http://cocodataset.org/#home)
    [20] T. Pevny, P. Bas, and J. Fridrich, Steganalysis by subtractive pixel adjacency matrix, IEEE T. Inf. Foren. Sec., 5 (2010), 215–224.
    [21] J. Kodovsky, J. Fridrich and V. Holub, Ensemble classifiers for steganalysis of digital media, IEEE T. Inf. Foren. Sec., 7 (2012), 432–444.
  • Reader Comments
  • © 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(4232) PDF downloads(895) Cited by(15)

Article outline

Figures and Tables

Figures(6)  /  Tables(4)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog