SSShaekh Hasan Shoron

Shaekh Hasan Shoron

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Shaekh Hasan Shoron has a total of 8 co-authors. Here are the top co-authors by number of shared publications:

  • Byungtae Jang

    Industry IT Convergence Research Group, Intelligent Robotics Research Division, SW Contents Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Korea

    1 shared publication
  • Dong-Sun Lim

    Industry IT Convergence Research Group, Intelligent Robotics Research Division, SW Contents Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Korea

    1 shared publication
  • Dongkoo Shon

    Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Republic of Korea

    1 shared publication
  • Jeong-Ho Park

    Industry IT Convergence Research Group, Intelligent Robotics Research Division, SW Contents Research Laboratory, Electronics and Telecommunications Research Institute (ETRI), Daejeon 34129, Korea

    1 shared publication
  • Jia Uddin

    Endicott College, Woosong University

    1 shared publication
  • Jong-Myon Kim

    Department of Electrical, Electronic and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea

    1 shared publication

Latest Publications

  • Open Access

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

    by Shaekh Hasan Shoron, Monamy Islam, Jia Uddin, Dongkoo Shon, Kichang Im, Jeong-Ho Park, Dong-Sun Lim, Byungtae Jang, Jong-Myon Kim

    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).