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A Heuristic Automatic and Robust ROI Detection Method for Medical Image Warermarking.

Seyed Mojtaba Mousavi1, Alireza Naghsh, S A R Abu-Bakar

  • 1Computer Vision, Video, and Image Processing (CvviP) Research Lab, Department of Electronics and Computer Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia, mosavi59@gmail.com.

Journal of Digital Imaging
|March 5, 2015
PubMed
Summary

This study introduces an automatic region of interest (ROI) segmentation method for robust medical image watermarking. The technique effectively preserves ROI integrity against various image attacks, ensuring reliable data protection.

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Area of Science:

  • Medical Imaging
  • Image Processing
  • Digital Watermarking

Background:

  • Medical image security is crucial for patient data integrity.
  • Existing watermarking methods may lack robustness against common image processing attacks.
  • Automatic region of interest (ROI) identification is needed for targeted watermarking.

Purpose of the Study:

  • To develop an automatic region of interest (ROI) segmentation method for medical image watermarking.
  • To evaluate the robustness of the proposed watermarking scheme against various image processing attacks.
  • To enhance the overall security and strength of the watermarking system.

Main Methods:

  • An automatic ROI detection system was developed.
  • The system's robustness was evaluated against median, Wiener, Gaussian, and sharpening filters.
  • An enhancement module was recommended to improve system resilience.

Main Results:

  • The proposed automatic ROI segmentation method demonstrated robustness against common image processing attacks.
  • The watermarking scheme maintained ROI integrity before and after various filtering attacks.
  • The method showed promising performance in securing medical images.

Conclusions:

  • The developed automatic ROI segmentation technique offers a robust solution for medical image watermarking.
  • The method ensures the integrity of critical image regions against common attacks.
  • This approach enhances the security and reliability of digital watermarking in healthcare.