Digital watermarking is a crucial technique for embedding and extracting hidden information in digital media, including medical images. Medical image authentication plays a critical role in ensuring the integrity and authenticity of digital medical images, which are essential for accurate diagnosis, treatment planning, and research. The project focuses on the development of a robust watermarking algorithm for medical image authentication using 3 different methods, including techniques like DWT, SVD, Hamming code. The methods aim to embed an imperceptible watermark into medical images, which can later be extracted to verify the authenticity and integrity of the images.

In conclusion, this project focused on developing various robust image watermarking techniques using Singular Value Decomposition (SVD) in the context of telemedicine. The rapid advancement of telemedicine has brought about the need for secure transmission and protection of medical images, ensuring patient privacy and data integrity. Through extensive research and experimentation, we developed different watermarking algorithms based on DWT, SVD, Hamming code, which proved to be effective in embedding imperceptible watermarks into medical images. These techniques not only provide robustness against common attacks but also maintain the visual quality and diagnostic information of the images.

The SVD-based watermarking algorithms demonstrated the ability to withstand various attacks such as compression, noise addition and cropping. This robustness is essential in telemedicine applications where medical images may be transmitted over unreliable networks or stored in vulnerable environments. Moreover, the project explored the trade-off between imperceptibility and robustness, considering factors such as embedding capacity, computational complexity, and visual quality degradation. The evaluation of these techniques was conducted using metrics such as Peak Signal-to-Noise Ratio (PSNR), Normalized Correlation Coefficient (NCC), and perceptual quality assessment.

Overall, this project contributes to the understanding and advancement of robust image watermarking techniques using SVD, providing valuable insights for securing medical images in telemedicine. By safeguarding the integrity and confidentiality of these images, we can foster trust, enable accurate diagnosis, and ultimately improve healthcare services in the telemedicine domain.