In this work, a blind watermarking framework for medical images based on Dual-Tree Complex Wavelet Transform (DTCWT) and Non-subsampled Contourlet Transform (NSCT) is proposed. The core idea of this technique is to embed the watermark in the appropriate NSCT sub-band obtained by decomposing the cover image low coefficients purchased from the DTCWT standing on a quantization embedding function, the extraction phase is done without the requirement of the original cover image, what makes it a fully blind process. As clarity and integrity of the retrieved watermark are mandatory, a series of tests were exerted to affirm the robustness of the proposed scheme. The effectiveness of the watermarking is validated by using the peak signal-to-noise ratio (PSNR) and the structural similarity index measure (SSIM) through experiments. Simulation results demonstrate the invisibility of the proposed method and its strong robustness against various attacks, including additive noise, image filtering, JPEG compression, amplitude scaling, rotation attack, and combinational attack. Furthermore, the method in hands outperformance within the quantitative comparisons with other techniques in the literature in terms of rapid execution time, and quality extraction of hidden information, and appropriateness to be integrated for secure exchange in the healthcare sector.
This study presents a combined watermarking-cryptography approach to bolster the security of biometric fingerprint data. In the initial stage, a digital watermark is embedded within the host image (fingerprint scan) using the Least Significant Bit (LSB) technique. Upon completion of the embedding process, the watermarked image undergoes encryption using the Advanced Encryption Standard (AES) in Cipher Block Chaining (CBC) mode, increasing complexity and ensuring secure communication. Conversely, the extraction procedure involves reversing the embedding steps by first decrypting the received image and subsequently applying the extraction algorithm to the unencrypted image to recover the embedded watermark. The proposed method demonstrates significant imperceptibility, as measured by the Peak Signal-to-Noise Ratio (PSNR) and Normalized Correlation (NCC) metrics. Furthermore, the watermark exhibits resilience against signal processing attacks, including noise and filtering. The heightened key sensitivity of the CBC cryptosystem renders the proposed scheme more resistant to statistical attacks compared to existing methods in the literature.
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