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A New Blind Medical Image Watermarking Based on Weber Descriptors and Arnold Chaotic Map

  • Research Article - Computer Engineering and Computer Science
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Abstract

Protecting the personal patient’s information in distributed health infrastructures seems to be a crucial task. As a solution of this issue, image watermarking is widely used to secure and prevent the content alteration. Moreover, it is necessary to find a new blind watermarking technique way that could decrease the latency and preserve the quality of medical images. This paper presents a new watermarking technique for medical image. Our technique consists in combining the DCT transform, Weber descriptors (WDs) and Arnold chaotic map. This combination brings three significant steps. First, the watermark image is scrambled using Arnold chaotic map. Second, the DCT is performed on each medical image block, and the watermark data are embedded in the DCT middle- band coefficients of each block. Finally, a new embedding and extracting technique is proposed, based on WDs without any loss by selecting the right coefficients. We improve the robustness of the proposed algorithm against several scenarios of attacks such as noising, filtering and JPEG compression. The obtained results make our algorithm eligible to be practicable.

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References

  1. Su, Q.; Niu, Y.; Wang, Q.; Sheng, G.: A blind color image watermarking based on DC component in the spatial domain. Opt. Int. J. Light Electron Optics 124(23), 6255–6260 (2013)

    Article  Google Scholar 

  2. Benoraira, A.; Benmahammed, K.; Boucenna, N.: Blind image watermarking technique based on differential embedding in DWT and DCT domains. EURASIP J. Adv. Signal Process. 1, 2015 (2015)

    Google Scholar 

  3. Rahmani, H.; Mortezaei, R.; Ebrahimi, M.M.: A new robust watermarking scheme to increase image security. EURASIP J. Adv. Signal Process. 2010(1), 428183 (2010)

    Article  Google Scholar 

  4. Liu, H.; Xiao, D.; Zhang, R.; Zhang, Y.; Bai, S.: Robust and hierarchical watermarking of encrypted images based on compressive sensing. Signal Process. Image Commun. 45, 41–51 (2016)

    Article  Google Scholar 

  5. Wang, X.; Liu, Y.; Xu, H.; Wang, A.; Yang, H.: Blind optimum detector for robust image watermarking in nonsubsampled shearlet domain. Inf. Sci. 372, 634–654 (2016)

    Article  Google Scholar 

  6. Kamran, K.A.; Malik, S.: A high capacity reversible watermarking approach for authenticating images: exploiting down-sampling, histogram processing, and block selection. Inf. Sci. 256, 162–183 (2014)

    Article  Google Scholar 

  7. Lakshmi Prasad, K.; Malleswara Rao, T.; Kannan, V.: A novel and hybrid secure digital image watermarking framework through sc-LWT-SVD. Indian J. Sci. Technol. 9(23), 1–10 (2016)

    Article  Google Scholar 

  8. Wang, C.; Wang, X.; Zhang, C.; Xia, Z.: Geometric correction based color image watermarking using fuzzy least squares support vector machine and Bessel K form distribution. Signal Process. 134, 197–208 (2017)

    Article  Google Scholar 

  9. Ghosal, S.; Mandal, J.: Binomial transform based fragile watermarking for image authentication. J. Inf. Secur. Appl. 19(4–5), 272–281 (2014)

    Google Scholar 

  10. Preda, R.: Semi-fragile watermarking for image authentication with sensitive tamper localization in the wavelet domain. Measurement 46(1), 367–373 (2013)

    Article  MathSciNet  Google Scholar 

  11. Panchal, U.H.; Srivastava, R.: A comprehensive survey on digital image watermarking techniques. In: Proceeding of the 5th International Conference on Communication Systems and Network Technologies (CSNT), IEEE, pp. 591–595, 4–6 April 2015

  12. Radharani, S.; Valarmathi, D.: A study on watermarking schemes for image authentication. Int. J. Comput. Appl. 2(4), 24–32 (2010)

    Google Scholar 

  13. Das, C.; Panigrahi, S.; Sharma, V.; Mahapatra, K.: A novel blind robust image watermarking in DCT domain using inter-block coefficient correlation. AEU Int. J. Electron. Commun. 68(3), 244–253 (2014)

    Article  Google Scholar 

  14. Mohammadi, S.: A semi blind watermarking algorithm for color image using chaotic map. In: Proceeding of the 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI), IEEE, pp. 106–110. Iran University of Science and Technology, Tehran, Iran, 5–6 November 2015

  15. Daraee, F.; Mozaffari, S.: Watermarking in binary document images using fractal codes. Pattern Recogn. Lett. 35, 120–129 (2014)

    Article  Google Scholar 

  16. Cooley, J.W.; Lewis, P.A.W.; Welch, P.D.: The finite Fourier transform. IEEE Trans. Audio Electroacoust. AU 17(2), 77 (1969)

    Article  MathSciNet  Google Scholar 

  17. Makhoul, J.: A fast cosine transform in one and two dimensions. IEEE Trans. Acoust. Speech Signal Process. ASSP 28(1), 27 (1980)

    Article  MathSciNet  Google Scholar 

  18. Heil, C.; Walnut, D.: Continuous and discrete wavelet transforms. SIAM Rev. 31(4), 628–666 (1989)

    Article  MathSciNet  Google Scholar 

  19. Kabra, R.G.; Agrawal, S.S.: Robust embedding of image watermark using LWT and SVD. In: Proceeding of the International Conference on Communication and Signal Processing, IEEE, India, pp. 1968–1972, 6–8 April 2016

  20. Mousavi, S.; Naghsh, A.; Abu-Bakar, S.: Watermarking techniques used in medical images: a survey. J. Digit. Imaging 27(6), 714–729 (2014)

    Article  Google Scholar 

  21. Dey, N.; Karaa, W.B.; Shakraborty, S.; Banerjee, S.; Salem, M.A.M.; Azar, A.T.: Image mining framework and techniques: a review. Int. J. Image Min. 1(1), 45–64 (2015)

    Article  Google Scholar 

  22. Zahradnikova, B.; Duchovicova, S.; Schreiber, P.: Image mining: review and new challenges. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 6(7), 367–373 (2015)

    Google Scholar 

  23. Várkonyi-Kóczy, A.R.: New advances in digital image processing. Memet. Comput. 2, 283–304 (2010)

    Article  Google Scholar 

  24. Martinez, J.M.; Koenen, R.; Pereira, F.: MPEG-7: the generic multimedia content description standard, part 1. MultiMed. IEEE 9(2), 78–87 (2002)

    Article  Google Scholar 

  25. Khan, A.; Siddiqa, A.; Munib, S.; Malik, S.: A recent survey of reversible watermarking techniques. Inf. Sci. 279, 251–272 (2014)

    Article  Google Scholar 

  26. Mishra, N.; Silakari, D.S.: Image mining in the context of content based image retrieval: a perspective. IJCSI Int. J. Comput. Sci. Issues 9(4), 98–107 (2012)

    Google Scholar 

  27. Rahmani, M.; Akbarizadeh, G.: Unsupervised feature learning based on sparse coding and spectral clustering for segmentation of synthetic aperture radar images. IET Comput. Vis. 9(5), 629–638 (2015)

    Article  Google Scholar 

  28. Akbarizadeh, G.; Moghaddam, A.E.: Detection of lung nodules in CT scans based on unsupervised feature learning and fuzzy inference. J. Med. Imaging Health Inf. 6(2), 477–483 (2016)

    Article  Google Scholar 

  29. Akbarizadeh, G.: Segmentation of SAR satellite images using cellular learning automata and adaptive chains. J. Remote Sens. Technol. 1(2), 44–51 (2013)

    Article  Google Scholar 

  30. Akbarizadeh, G.; Rahmani, M.: Efficient combination of texture and color features in a new spectral clustering method for PolSAR image segmentation. Natl. Acad. Sci. Lett. 40(2), 117–120 (2017)

    Article  MathSciNet  Google Scholar 

  31. Modava, M.; Akbarizadeh, G.: A level set based method for coastline detection of SAR images. In: Proceedings of 3rd International on Pattern Recognition and Image Analysis (IPRIA) (2017)

  32. Andekah, Z.A.; Naderan, M.; Akbarizadeh, G.: Semi-supervised hyperspectral image classification using spatial-spectral features and superpixel-based sparse codes. In: Iranian Conference on Electrical Engineering (ICEE), pp. 2229–2234 (2017)

  33. Ahmadi, N.; Akbarizadeh, G.: Hybrid robust iris recognition approach using iris image pre-processing, two-dimensional Gabor features and multi-layer perceptron neural network/PSO. IET Biom. 7(2), 153–162 (2018)

    Article  Google Scholar 

  34. Faraji, Z.; Akbarizadeh, G.: A new computer vision algorithm for classification of POLSAR images. In: Proceedings of 7th Conference on Information and Knowledge Technology (IKT), pp. 1–4 (2015)

  35. Akbarizadeh, G.; Rahmani, M.: A new ensemble clustering method for PolSAR image segmentation. In: Proceedings of the 7th Conference on Information and Knowledge Technology (IKT), pp. 1–4 (2015)

  36. Akbarizadeh, G.; Tirandaz, Z.; Kooshesh, M.: A new curvelet-based texture classification approach for land cover recognition of SAR satellite images. Malays. J. Comput. Sci. 27(3), 218–239 (2014)

    Google Scholar 

  37. Laouamer, L.; Tayan, O.: A semi-blind robust DCT watermarking approach for sensitive text images. Arab. J. Sci. Eng. 40(4), 1097–1109 (2015)

    Article  Google Scholar 

  38. Mansoori, E.; Soltani, S.: A new semi-blind watermarking algorithm using ordered Hadamard transform. Imaging Sci. J. 64(4), 204–214 (2016)

    Article  Google Scholar 

  39. Roy, S.; Pal, A.: A blind DCT based color watermarking algorithm for embedding multiple watermarks. AEU Int. J. Electron. Commun. 72, 149–161 (2017)

    Article  Google Scholar 

  40. Wang, J.; Liu, Y.: Schur decomposition based robust watermarking algorithm in contourlet domain. In: Proceeding of the International Conference on Cloud Computing and Security (ICCCS), Part I, pp. 114–124. Springer (2016)

  41. Singh, D.; Singh, S.: DWT-SVD and DCT based robust and blind watermarking scheme for copyright protection. Multimed. Tools Appl. 76, 13001 (2016)

    Article  Google Scholar 

  42. Zhao, J.; Xu, W.; Zhang, S.; Fan, S.; Zhang, W.: A strong robust zero-watermarking scheme based on shearlets high ability for capturing directional features. Math. Probl. Eng. 2016, 1–11 (2016)

    Google Scholar 

  43. Singh, A.; Dave, M.; Mohan, A.: Hybrid technique for robust and imperceptible multiple watermarking using medical images. Multimed. Tools Appl. 75(14), 8381–8401 (2015)

    Article  Google Scholar 

  44. Ghadi, M.; Laouamer, L.; Nana, L.; Pascu, A.: A novel zero-watermarking approach of medical images based on Jacobian matrix model. Secur. Commun. Netw. 9, 1–16 (2016)

    Article  Google Scholar 

  45. Awrangjeb, M.; Kankanhalli, M.S.: Reversible watermarking using a perceptual model. SPIE J. Electron. Imaging 14(1), 1–8 (2005)

    Google Scholar 

  46. Awrangjeb, M.; Lu, G.: A robust content-based watermarking technique. In: Proceedings of International Workshop on Multimedia Signal Processing (MMSP 2008), Queensland, Australia, pp. 563–568, 8–10 October 2008

  47. Awrangjeb, M.; Hossain, M. S.: A hierarchical security solution for medical image transmissions. In: Proceedings of the International Conference on Computer and Information Technology (ICCIT 2004), Bangladesh, pp. 435–441, December 2004

  48. Rani, A.; Raman, B.; Kumar, S.: A robust watermarking scheme exploiting balanced neural tree for rightful ownership protection. Multimed. Tools Appl. 72(3), 2225–2248 (2013)

    Article  Google Scholar 

  49. Abdelhakim, A.; Saleh, H.; Nassar, A.: A quality guaranteed robust image watermarking optimization with artificial bee colony. Expert Syst. Appl. 72, 317–326 (2017)

    Article  Google Scholar 

  50. Moghaddam, M.; Nemati, N.: A robust color image watermarking technique using modified imperialist competitive algorithm. Forensic Sci. Int. 233(1–3), 193–200 (2013)

    Article  Google Scholar 

  51. AL-Nabhani, Y.; Jalab, H.; Wahid, A.; Noor, R.: Robust watermarking algorithm for digital images using discrete wavelet and probabilistic neural network. J. King Saud Univ. Comput. Inf. Sci. 27(4), 393–401 (2015)

    Google Scholar 

  52. Arsalan, M.; Qureshi, A.; Khan, A.; Rajarajan, M.: Protection of medical images and patient related information in healthcare: using an intelligent and reversible watermarking technique. Appl. Soft Comput. 51, 168–179 (2017)

    Article  Google Scholar 

  53. Chen, J.; Shan, S.; Zhao, G.; Chen, X.; Gao, W.; Pietikäinen, M.: A robust descriptor based on Weber’s law. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, pp. 1–7 (2008)

  54. Lazoff, M.; Cadogan, M.: Life in the Fastlane, LITFL review 236. http://lifeinthefastlane.com/resources/radiology-database/

  55. Petitcolas, F.: Watermarking stirmark. http://w.petitcolas.net/fabien/watermarking/stirmark/ (2012)

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Soualmi, A., Alti, A. & Laouamer, L. A New Blind Medical Image Watermarking Based on Weber Descriptors and Arnold Chaotic Map. Arab J Sci Eng 43, 7893–7905 (2018). https://doi.org/10.1007/s13369-018-3246-7

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  • DOI: https://doi.org/10.1007/s13369-018-3246-7

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