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Volume 8
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Article

A Watermarking Technique for Biomedical Images Using SMQT, Otsu, and Fuzzy C-Means

by
Shaekh Hasan Shoron
1,
Monamy Islam
1,
Jia Uddin
1,
Dongkoo Shon
2,
Kichang Im
3,
Jeong-Ho Park
4,
Dong-Sun Lim
4,
Byungtae Jang
4 and
Jong-Myon Kim
2,*
1
Department of Computer Science and Engineering, Brac University, Mohakhali, Dhaka 1212, Bangladesh
2
School of IT Convergence, University of Ulsan, Ulsan 44610, Korea
3
ICT Convergence Safety Research Center, University of Ulsan, Ulsan 44610, Korea
4
Industry IT Convergence Research Group, SW Contents Research Laboratory, Intelligent Robotics Research Division, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Korea
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(9), 975; https://doi.org/10.3390/electronics8090975
Submission received: 14 July 2019 / Revised: 28 August 2019 / Accepted: 29 August 2019 / Published: 31 August 2019
(This article belongs to the Special Issue Recent Advances in Biometrics and its Applications)
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Abstract

Digital watermarking is a process of giving security from unauthorized use. To protect the data from any kind of misuse while transferring, digital watermarking is the most popular authentication technique. This paper proposes a novel digital watermarking scheme for biomedical images. In the model, initially, the biomedical image is preprocessed using improved successive mean quantization transform (SMQT) which uses the Otsu’s threshold value. In the next phase, the image is segmented using Otsu and Fuzzy c-means. Afterwards, the watermark is embedded in the image using discrete wavelet transform (DWT) and inverse DWT (IDWT). Finally, the watermark is extracted from the biomedical image by executing the inverse operation of the embedding process. Experimental results exhibit that the proposed digital watermarking scheme outperforms the typical models in terms of effectiveness and imperceptibility while maintaining robustness against different attacks by demonstrating a lower bit error rate (BER), a cross-correlation value closer to one, and higher values of structural similarity index measures (SSIM) and peak signal-to-noise ratio (PSNR).
Keywords: digital watermarking; biomedical image; successive mean quantization transform; Fuzzy c-means cluster; confidentiality; robustness; imperceptibility digital watermarking; biomedical image; successive mean quantization transform; Fuzzy c-means cluster; confidentiality; robustness; imperceptibility

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MDPI and ACS Style

Shoron, S.H.; Islam, M.; Uddin, J.; Shon, D.; Im, K.; Park, J.-H.; Lim, D.-S.; Jang, B.; Kim, J.-M. A Watermarking Technique for Biomedical Images Using SMQT, Otsu, and Fuzzy C-Means. Electronics 2019, 8, 975. https://doi.org/10.3390/electronics8090975

AMA Style

Shoron SH, Islam M, Uddin J, Shon D, Im K, Park J-H, Lim D-S, Jang B, Kim J-M. A Watermarking Technique for Biomedical Images Using SMQT, Otsu, and Fuzzy C-Means. Electronics. 2019; 8(9):975. https://doi.org/10.3390/electronics8090975

Chicago/Turabian Style

Shoron, Shaekh Hasan, Monamy Islam, Jia Uddin, Dongkoo Shon, Kichang Im, Jeong-Ho Park, Dong-Sun Lim, Byungtae Jang, and Jong-Myon Kim. 2019. "A Watermarking Technique for Biomedical Images Using SMQT, Otsu, and Fuzzy C-Means" Electronics 8, no. 9: 975. https://doi.org/10.3390/electronics8090975

APA Style

Shoron, S. H., Islam, M., Uddin, J., Shon, D., Im, K., Park, J.-H., Lim, D.-S., Jang, B., & Kim, J.-M. (2019). A Watermarking Technique for Biomedical Images Using SMQT, Otsu, and Fuzzy C-Means. Electronics, 8(9), 975. https://doi.org/10.3390/electronics8090975

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