Original scientific paper
https://doi.org/10.1080/00051144.2023.2187525
Zero watermarking scheme for privacy protection in e-Health care
Ayesha Shaik
; School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India
*
V. Masilamani
; Department of Computer Engineering, Indian Institute of Information Technology Design, and Manufacturing Kancheepuram (IIITDMK), Chennai, India
* Corresponding author.
Abstract
E-health care is an emerging field where health services and information are delivered and offered over the Internet. So the health information of the patients communicated over the Internet has to protect the privacy of the patients. The patient information is embedded into the health record and communicated online which also induces degradation to the original information. So, in this article, a zero watermarking scheme for privacy protection is proposed which protects the privacy and also eliminates the degradation done during embedding of patient information into the health record. This method is based on simple linear iterative clustering (SLIC) superpixels and partial pivoting lower triangular upper triangular (PPLU) factorization. The novelty of this article is that the use of SLIC superpixels and PPLU decomposition for the privacy protection of medical images (MI). The original image is subjected to SLIC segmentation and non-overlapping high entropy blocks are selected. On the selected blocks discrete wavelet transform (DWT) is applied and those blocks undergo PPLU factorization to get three matrices, L, U and P, which are lower triangular, upper triangular and permutation matrix respectively. The product matrix L×U
is used to construct a zero-watermark. The technique has been experimented on the UCID, BOWS and SIPI databases. The test results demonstrate that this work shows high robustness which is measured using normalized correlation (NC) and bit error rate (BER) against the listed attacks.
Keywords
Zero watermarking; PPLU decomposition; DWT; health care; privacy protection; SLIC segmentation
Hrčak ID:
315763
URI
Publication date:
18.3.2023.
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