In order to improve the robustness of the differential number watermarking (DNW) algorithm proposed by us before, we proposed turbo-based DNW (T-DNW) in which the turbo code was employed in the DNW algorithm. The turb...In order to improve the robustness of the differential number watermarking (DNW) algorithm proposed by us before, we proposed turbo-based DNW (T-DNW) in which the turbo code was employed in the DNW algorithm. The turbo code was used to encode the message prior to watermark embedding and decode the watermark posterior to watermark detection. From the analysis and experiments, the following conclusion could be drawn. The T-DNW algorithm has little higher computational complexity than DNW. And both algorithms have the same performance in terms of watermark visual quality impact. Furthermore, the T-DNW algorithm is much more robust against some common attack than DNW. Although the T-DNW algorithm sacrifices a half payload, we think the achievements are encouraging.展开更多
Phonocardiogram （PCG）, the digital recording of heart sounds is becoming increasingly popular as a primary detection system for diagnosing heart disorders and it is relatively inexpensive. Electrocardiogram （ECG） ...Phonocardiogram （PCG）, the digital recording of heart sounds is becoming increasingly popular as a primary detection system for diagnosing heart disorders and it is relatively inexpensive. Electrocardiogram （ECG） is used during the PCG in order to identify the systolic and diastolic parts manually. In this study a heart sound segmentation algorithm has been developed which separates the heart sound signal into these parts automa- tically. This study was carried out on 100 patients with normal and abnormal heart sounds. The algorithm uses discrete wavelet decomposition and reconstruction to pro- duce PCG intensity envelopes and separates that into four parts： the first heart sound, the systolic period, the second heart sound and the diastolic period. The performance of the algorithm has been evaluated using 14,000 cardiac periods from 100 digital PCG recordings, including normal and abnormal heart sounds. In tests, the algorithm was over93% correct in detecting the first and second heart sounds. The presented automatic seg- mentation Mgorithm using w^velet decomposition and reconstruction to select suitable frequency band for envelope calculations has been found to be effective to segment PCG signals into four parts without using an ECG.展开更多
文摘In order to improve the robustness of the differential number watermarking (DNW) algorithm proposed by us before, we proposed turbo-based DNW (T-DNW) in which the turbo code was employed in the DNW algorithm. The turbo code was used to encode the message prior to watermark embedding and decode the watermark posterior to watermark detection. From the analysis and experiments, the following conclusion could be drawn. The T-DNW algorithm has little higher computational complexity than DNW. And both algorithms have the same performance in terms of watermark visual quality impact. Furthermore, the T-DNW algorithm is much more robust against some common attack than DNW. Although the T-DNW algorithm sacrifices a half payload, we think the achievements are encouraging.
文摘Phonocardiogram （PCG）, the digital recording of heart sounds is becoming increasingly popular as a primary detection system for diagnosing heart disorders and it is relatively inexpensive. Electrocardiogram （ECG） is used during the PCG in order to identify the systolic and diastolic parts manually. In this study a heart sound segmentation algorithm has been developed which separates the heart sound signal into these parts automa- tically. This study was carried out on 100 patients with normal and abnormal heart sounds. The algorithm uses discrete wavelet decomposition and reconstruction to pro- duce PCG intensity envelopes and separates that into four parts： the first heart sound, the systolic period, the second heart sound and the diastolic period. The performance of the algorithm has been evaluated using 14,000 cardiac periods from 100 digital PCG recordings, including normal and abnormal heart sounds. In tests, the algorithm was over93% correct in detecting the first and second heart sounds. The presented automatic seg- mentation Mgorithm using w^velet decomposition and reconstruction to select suitable frequency band for envelope calculations has been found to be effective to segment PCG signals into four parts without using an ECG.
