A blind and high-capacity data hiding of DICOM medical images based on fuzzification concepts

Data hiding technique using steganography prospered widely due to its high undetectability, flexibility to the size of hidden data, and robustness against compression and other image processes. Accordingly, this paper aims to use a steganographic technique based on DICOM medical images, where one medical image is used as a cover image, and the other one is used as the secret message image. This method entails three main parts: preprocessing, data embedding based on the discrete cosine transform (DCT), and an extraction process. The performances of the algorithm were evaluated using Magnetic resonance imaging (MRI) dataset, the metrics of the Peak Signal to Noise Ratio (PSNR), the Mean Square Error (MSE), the Structural Similarity Index (SSIM), the Universal Quality Index (UQI), and the correlation coefficient (R) values. The experimental results scored a high PSNR after the embedding process and high capacity of the hidden data by embedding a DICOM image into another DICOM image of the same size. (C) 2020 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.

Automated summary

The study utilizes DICOM medical images as carriers to hide data using steganography, achieving high capacity and PSNR values for the hidden data.