Combinational Watermarking for Medical Images
Digitization of medical data has become a very important part of the modern healthcare system. Data can be transmitted easily at any time to anywhere in the world using Internet to get the best diagnosis possible for a patient. This digitized medical data must be protected at all times to preserve t...
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ndltd-USF-oai-scholarcommons.usf.edu-etd-70372018-03-28T06:01:37Z Combinational Watermarking for Medical Images Chakravarthy Chinna Narayana Swamy, Thrilok Digitization of medical data has become a very important part of the modern healthcare system. Data can be transmitted easily at any time to anywhere in the world using Internet to get the best diagnosis possible for a patient. This digitized medical data must be protected at all times to preserve the doctor-patient confidentiality. Watermarking can be used as an effective tool to achieve this. In this research project, image watermarking is performed both in the spatial domain and the frequency domain to embed a shared image with medical image data and the patient data which would include the patient identification number. For the proposed system, Structural Similarity (SSIM) is used as an index to measure the quality of the watermarking process instead of Peak Signal to Noise Ratio (PSNR) since SSIM takes into account the visual perception of the images compared to PSNR which uses the intensity levels to measure the quality of the watermarking process. The system response under ideal conditions as well as under the influence of noise were measured and the results were analyzed. 2015-01-01T08:00:00Z text application/pdf http://scholarcommons.usf.edu/etd/5833 http://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=7037&context=etd default Graduate Theses and Dissertations Scholar Commons Wavelet Transform Spatial Domain Structural Similarity Normalized Correlation Shared Key Electrical and Computer Engineering |
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Wavelet Transform Spatial Domain Structural Similarity Normalized Correlation Shared Key Electrical and Computer Engineering |
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Wavelet Transform Spatial Domain Structural Similarity Normalized Correlation Shared Key Electrical and Computer Engineering Chakravarthy Chinna Narayana Swamy, Thrilok Combinational Watermarking for Medical Images |
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Digitization of medical data has become a very important part of the modern healthcare system. Data can be transmitted easily at any time to anywhere in the world using Internet to get the best diagnosis possible for a patient. This digitized medical data must be protected at all times to preserve the doctor-patient confidentiality. Watermarking can be used as an effective tool to achieve this.
In this research project, image watermarking is performed both in the spatial domain and the frequency domain to embed a shared image with medical image data and the patient data which would include the patient identification number.
For the proposed system, Structural Similarity (SSIM) is used as an index to measure the quality of the watermarking process instead of Peak Signal to Noise Ratio (PSNR) since SSIM takes into account the visual perception of the images compared to PSNR which uses the intensity levels to measure the quality of the watermarking process. The system response under ideal conditions as well as under the influence of noise were measured and the results were analyzed. |
author |
Chakravarthy Chinna Narayana Swamy, Thrilok |
author_facet |
Chakravarthy Chinna Narayana Swamy, Thrilok |
author_sort |
Chakravarthy Chinna Narayana Swamy, Thrilok |
title |
Combinational Watermarking for Medical Images |
title_short |
Combinational Watermarking for Medical Images |
title_full |
Combinational Watermarking for Medical Images |
title_fullStr |
Combinational Watermarking for Medical Images |
title_full_unstemmed |
Combinational Watermarking for Medical Images |
title_sort |
combinational watermarking for medical images |
publisher |
Scholar Commons |
publishDate |
2015 |
url |
http://scholarcommons.usf.edu/etd/5833 http://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=7037&context=etd |
work_keys_str_mv |
AT chakravarthychinnanarayanaswamythrilok combinationalwatermarkingformedicalimages |
_version_ |
1718617520073605120 |