A non-subsampled Shearlet transform based approach for heartbeat sound watermarking. (January 2022)

• Record Type: Journal Article
• Authors: Moad, Med Sayah; Kafi, Med Redouane; Khaldi, Amine
• Is Part Of: Biomedical signal processing and control. Volume 71(2022)Part A
• Publication Date: 2022-01
• Subjects: Digital watermarking -- Medical heartbeat sound -- Non-subsampled Shearlet Transform -- Singular value decomposition -- Arnold transform; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2021.103114
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: In this paper, we propose a blind watermarking approach for the heartbeat sound exchanged in telemedicine. This approach allows guaranteeing the patients' authentication by integrating a watermark containing the patient's information as well as his photography in the audio file. The proposed approach combining a Non-Subsampled Shearlet Transform and Singular Value Decomposition. The imperceptibility results have shown that we can integrate a satisfactory amount of information while preserving the diagnostic content of the audio file. Abstract: To secure the heartbeat sound exchanged in telemedicine, we propose in this work a blind watermarking approach combining a Non-Subsampled Shearlet Transform and Singular Value Decomposition. This approach allows guaranteeing the patients' successful authentication by integrating a watermark containing the patient's specific information as well as his photography in the audio file. In this approach to decompose the signal into low and high frequencies, a Non-Subsampled Shearlet Transform is performed. Singular value decomposition is then applied to the obtained low frequency components and the watermark bits are integrated by modulating the singular values. The imperceptibility results have typically shown our approach can integrate a satisfactory amount of information while preserving the diagnostic content of the audio file. In addition, the robustness tests demonstrate the proposed approach can efficiently generate a watermark resisting to several attacks. The imperceptibility results have shown our approach can integrate a satisfactory amount of necessary information while preserving the diagnostic content of the audio file. Since the patient informations are embedded in the multimedia file, a watermark extraction will clearly authenticate the potential patient. Since the patient informations are embedded in the multimedia file, a watermark extraction will clearly authenticate the patient.