A Wavelet-Based Digital Watermarking Technique for ECG Signals

碩士 === 東海大學 === 應用數學系 === 101 === In nowadays society, we pay much attention to a variety of copyright protection issues and the emphasis on personal information. Digital watermarking technology is the most widely used encryption technology in the field of multi-media and medical information. In thi...

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Main Authors: GUO,YUAN-JIE, 郭元傑
Other Authors: HUANG,HUANG-NAN
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/09223596464019777413
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spelling ndltd-TW-101THU005070012015-10-13T22:23:54Z http://ndltd.ncl.edu.tw/handle/09223596464019777413 A Wavelet-Based Digital Watermarking Technique for ECG Signals 心電訊號之小波浮水印技術 GUO,YUAN-JIE 郭元傑 碩士 東海大學 應用數學系 101 In nowadays society, we pay much attention to a variety of copyright protection issues and the emphasis on personal information. Digital watermarking technology is the most widely used encryption technology in the field of multi-media and medical information. In this thesis, we redesign a wavelet-based digital watermark to Electrocardiogram (ECG) signals to achieve the purpose of protection of patient rights. Certain hidden data for personnel identification are embedded into specified low-frequency coefficients of its wavelet transform according to different quantization sizes using the quantization approach. In addition, since the proposed watermark scheme is not reversible, we evaluate the impact of watermarking to the PQRST complexes of the ECG signal in which we conclude that the impact is small and the watermarked data can meet the requirement of physiological diagnostics. In order to measure the robustness of our scheme, three attacks including noise, resampling, and low-pass filter are adopted to test the watermarked ECG data. The experimental result verifies that the proposed scheme is slightly robust than DCT- and FFT-implemented quantization watermarking techniques after testing with ECG signals from the MIT-BIH arrhythmia database. HUANG,HUANG-NAN 黃皇男 2013 學位論文 ; thesis 49 zh-TW
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description 碩士 === 東海大學 === 應用數學系 === 101 === In nowadays society, we pay much attention to a variety of copyright protection issues and the emphasis on personal information. Digital watermarking technology is the most widely used encryption technology in the field of multi-media and medical information. In this thesis, we redesign a wavelet-based digital watermark to Electrocardiogram (ECG) signals to achieve the purpose of protection of patient rights. Certain hidden data for personnel identification are embedded into specified low-frequency coefficients of its wavelet transform according to different quantization sizes using the quantization approach. In addition, since the proposed watermark scheme is not reversible, we evaluate the impact of watermarking to the PQRST complexes of the ECG signal in which we conclude that the impact is small and the watermarked data can meet the requirement of physiological diagnostics. In order to measure the robustness of our scheme, three attacks including noise, resampling, and low-pass filter are adopted to test the watermarked ECG data. The experimental result verifies that the proposed scheme is slightly robust than DCT- and FFT-implemented quantization watermarking techniques after testing with ECG signals from the MIT-BIH arrhythmia database.
author2 HUANG,HUANG-NAN
author_facet HUANG,HUANG-NAN
GUO,YUAN-JIE
郭元傑
author GUO,YUAN-JIE
郭元傑
spellingShingle GUO,YUAN-JIE
郭元傑
A Wavelet-Based Digital Watermarking Technique for ECG Signals
author_sort GUO,YUAN-JIE
title A Wavelet-Based Digital Watermarking Technique for ECG Signals
title_short A Wavelet-Based Digital Watermarking Technique for ECG Signals
title_full A Wavelet-Based Digital Watermarking Technique for ECG Signals
title_fullStr A Wavelet-Based Digital Watermarking Technique for ECG Signals
title_full_unstemmed A Wavelet-Based Digital Watermarking Technique for ECG Signals
title_sort wavelet-based digital watermarking technique for ecg signals
publishDate 2013
url http://ndltd.ncl.edu.tw/handle/09223596464019777413
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