RETRACTED ARTICLE: Robust and efficient image watermarking technology in big multimedia data environmental

• Published in: Multimedia tools and applications Vol. 79; no. 13-14; p. 9681
• Main Authors: Zhen-tao, Hu, Wang, Zepeng
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-04-2020; Springer Nature B.V
• Subjects: Computer Communication Networks; Computer Science; Data Structures and Information Theory; Medical imaging; Multimedia; Multimedia Information Systems; Special Purpose and Application-Based Systems; Multimedia; Image Watermarking Technology; Information Theory; RETRACTED ARTICLE; Peer Review Process
• ISSN: 1380-7501; 1573-7721
• DOI: 10.1007/s11042-017-5442-y

Over the past ten years, the use of medical imaging and electronic medical records (EPR) in the medical sector has been exponential in sharing and exchanging patient information between networked hospitals and related medical centers. Various digital watermarking techniques are being deployed to ensure confidentiality and security of medical images and information, which are stored or distributed in the medical department. The concept of this paper embeds EPR information on medical images to reduce storage space and transmission overhead, greatly reducing guaranteed data sharing techniques. In this paper, the ROI (region of interest) Lossless Medical Image Watermarking (MIW) technique and EPR are used to embed the medical image coefficients in the discrete cosine transform (DCT) median frequency band. Fuzzy C means (FCM) segmentation method is used to extract ROI. Before embedding, the patient’s information, a binary logo watermark, is improved by convolutional error correction coding (ECC) and M-ary modulation, which improves the robustness of the algorithm. The success of this approach has been demonstrated and validated by a variety of medical imaging methods: magnetic resonance angiography, magnetic resonance imaging, Radiology, and CT, and the results show no significant difference between the original watermark images. This watermarking method is robust to common attacks such as JPEG encoding, noise adding, histogram equalization, filtering, blurring, rotation and cropping. The improvement in robustness is demonstrated in the case of bit error rates in JPEG compression operations, using convolutional encoder coding calculations.