Dual Watermarking of Medical Images with Private Patient Information Based on Contourlet Transform

Document Type : Original Article(s)

Authors

1 Department of Biomedical Engineering, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

2 Assistant Professor, Department of Biomedical Engineering, School of Medicine AND Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

3 Assistant Professor, Department of Biomedical Engineering, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

Abstract

Background: Advances in information and communication technologies and quick growth in using the Internet on one hand, and changing of medical equipment from analog to digital as well as modified appearance of modern healthcare system, on the other, cause more attention to telemedicine in health care centers. The transmission and storage of medical images in health care centers has a standard file format (DICOM). Since data is exchanged between these centers via ordinary commercial information transmitting channels like the Internet, new problems like issuance of patient information or malicious modification can occur. Watermarking is one of the new techniques used to solve this problem. Digital watermarking can imperceptibly embed patient information without changing image size or format. Watermarking has various techniques, but blind method and transform-based techniques are more popular.Methods: In this research, we introduced a new blind contourlet-based watermarking technique. Images were divided into a region of interest (ROI) and a region of non-interest (RONI) and dual watermarking was used. After applying contourlet transform, the blocks were formed using coefficients of low level subband. For storing one bit in a selected block, the average of coefficients of each block was quantized to odd or even and appropriate procedures were used.Findings: Different techniques such as peak signal-to-noise ratio (PSNR), bit error rate (BER), and structural similarity index measure (SSIM) demonstrated the efficiency of the proposed method.

Keywords

References

  1. Raul RC, Claudia FU, Trinidad-Bias GJ. Data hiding scheme for medical image. Proceedings of the 17th International Conference on Electronics, Communications and Computers; 2007 Feb 26-28; Cholula, Puebla. p. 32-5.
  2. Coatrieux G, Maitre H, Sankur B, Rolland Y, Collorec R. Relevance of watermarking in medical imaging. Proceedings of the International Conference on Information Technology Applications in Biomedicine; 2000 Nov 9-10; Arlington, USA. p. 250-55.
  3. Coatrieux G, Quantin C, Montagner J, Fassa M, Allaert FA, Roux C. Watermarking medical images with anonymous patient identification to verify authenticity. Stud Health Technol Inform 2008; 136: 667-72.
  4. Pastorfide E, lores G. An image steganography algorithm for 24-bit color images using edge detection filter. Institute Of Computer Science 2006; 1-5.
  5. Li H, Song W, Wang SH. A novel blind watermarking algorithm in contourlet domain. Proceedings of the 18th International Conference in Pattern Recognition; 2006 Aug 20-24; Hong Kong, China. p. 639-42.
  6. Thangavel P, Kumaran T. Fragile watermark for tamper detection using structural distortion measure. IEEE International Symposium industrial Electronics; 2007 June 4-7; Vigo, Spain. p. 1755 - 60.
  7. Sheng-he S, Zhe-ming L, Xia-mu N. Digital watermarking technique and application. Beijing, China: Science Press; 2004.
  8. Zhu G, Sang N. Watermarking algorithm research and implementation based on DCT block. Proceedings of the conference World Academy of Science, Engineeringand Technology; 2008; p. 38-42.
  9. Zain JM, Fauzi ARM, Aziz AA. Clinical Evaluation of Watermarked Medical Images. Proceedings of the 28th IEEE EMBS Annual International Conference on Engineering in Medicine and Biology Society; 2006 Aug 30-Sep 3; New York, NY, USA. p. 5459 - 62.
  10. Zain JM, Fauzi ARM. Evaluation of Medical Image Watermarking with Tamper Detection and Recovery (AW-TDR). Proceedings of the 29th Annual International Conference of the IEEE EMBS on Engineering in Medicine and Biology Society; 2007 Aug 22-26; Lyon, France. p. 5661-64.
  11. Zain JM, Clarke M. Reversible Region of Non-Interest (RONI) Watermarking for Authentication of DICOM Images. International Journal of Computer Science and Network Security 2007; 7(9): 19-28.
  12. Do MN, Vetterli M. Contourlets: a directional multiresolution image representation. Proceeding of the International Conference on Image Processing; 2002; Urbana, IL, USA. p. 357-60.
  13. Li H, Song W, Wang SH. A novel blind watermarking algorithm in contourlet domain. Proceedings of the 18th International Conference on Pattern Recognition; 2006; Hong Kong, China. p. 639 - 42.
  14. Eslami R, Radha H. The contourlet transform for image denoising using cycle spinning. Proceedings of the 37th Asilomar Conference on Signals, Systems and Computers; 2003 Nov 9-12; Pacific Grove, CA, USA. p. 1982-86.
  15. Shu ZH, Wang SH, Deng CH, Liu G, Zhang L. Watermarking Algorithm based on Contourlet Transform and Human Visual Model. Proceedings of the International Conference on Embedded Software and Systems; 2008 July 29-31; Sichuan, China. p. 348 - 52.
  16. Zhang ZH, Huang W, Zhang J, Yu H, Lu Y. Digital Image Watermark Algorithm in the Curvelet Domain. Proceedings of the International Conference on Intelligent Information Hiding and Multimedia Signal Processing; 2006 Dec; Pasadena, CA, USA. p. 105-108.
  17. Petitcolas FAP. Watermarking schemes evaluation. Signal Processing Magazine 2000; 17(5): 58-64.
  18. Xiao SH, Ling H, Zou F, Lu ZH. Adaptive image watermarking algorithm in contourlet domain. Proceedings of the workshop on Frontier of Computer Science and Technology; 2007 Nov 1-3; Wuhan, China; p. 125-30.
Journal of Isfahan Medical School
Volume 29, Issue 174 - Serial Number 174
November and December 2011
Pages 3240-3250

Files

History

  • Receive Date: 05 May 2012
  • Revise Date: 20 April 2024
  • Accept Date: 06 April 2022

Share

How to cite

Statistics