Title: Improved Automatic and Robust ROI Detection Technique for Medical Image Watermarking Application | ||
Author(s): Seyed Mojtaba Mousavi, Alireza Naghsh, Azizah A. Manaf, S. A. R. Abu-Bakar | ||
Pages: 1-6 | Paper ID:164003-8181-IJVIPNS-IJENS | Published: June, 2016 |
Abstract: An image authentication scheme called watermarking is suggested to protect patients’ privacy by preventing patient documents from unauthorised access. In watermarking of medical image, in order to retain the quality of a region used for diagnostic purpose, known as Region of Interest (ROI), a prior knowledge about this area is needed. Most current medical watermarking schemes detect the ROI manually by assigned polygons or rectangles. In addition, in current automatic ROI detection algorithms, the robustness of ROI detection process is not being considered and addressed. It means the algorithms cannot tolerate any changes in the content of the medical images via any intentional or un-intentional attacks and the ROI detection algorithm is not efficient. By distributing and sharing the medical images between specialists and hospitals, they will be more vulnerable to different attacks. One of these potential attacks that may corrupt the medical images through transmission in communication channels is salt and pepper noise. In this paper an automatic ROI segmentation method for medical images watermarking application is proposed, which is robust against salt and pepper noise as a possible attack. Experimental results shows satisfactory performance of ROI segmentation under different densities of salt and pepper noise.
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Keywords: ROI detection; salt and pepper noise; medical images; robustness. | ||
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