A secure framework for medical image by integrating watermarking and encryption through fuzzy based ROI selection

Author:

Shamia D.1,Balasamy K.2,Suganyadevi S.3

Affiliation:

1. Department of ECE, VSB College of Engineering Technical Campus, Coimbatore

2. Department of AI & DS, Bannari Amman Institute of Technology, Sathyamangalam, Erode

3. Department of ECE, KPR Institute of Engineering and Technology, Coimbatore

Abstract

Security, secrecy, and authenticity problems have arisen as a result of the widespread sharing of medical images in social media. Copyright protection for online photo sharing is becoming a must. In this research, a cutting-edge method for embedding encrypted watermarks into medical images is proposed. The proposed method makes use of fuzzy-based ROI selection and wavelet-transformation to accomplish this. In the first step of the process, a fuzzy search is performed on the original picture to locate relevant places using the center region of interest (RoI) and the radial line along the final intensity. The suggested method takes a digital picture and divides it into 4×4 non-overlapping blocks, with the intent of selecting low information chunks for embedding in order to maximize invisibility. By changing the coefficients, a single watermark bit may be inserted into both the left and right singular SVD matrices. The absence of false positives means the suggested technique can successfully integrate a large amount of data. Watermarks are encrypted using a pseudorandom key before being embedded. Discrete wavelet transform saliency map, block mean method, and cosine functions are used to construct an adaptively-generated pseudo-random key from the cover picture. Images uploaded to social media platforms must have a high degree of invisibility and durability. These watermarking features, however, come with a price. The optimal scaling factor is used to strike a balance between the two in the proposed system. Furthermore, the suggested scheme’s higher performance is confirmed by comparison with the latest state-of-the-art systems.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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