Image Authentication based on Histogram Shifting method using Arnold’s Cat Map

Digital watermarking is a crucial technique for embedding and extracting hidden information in digital media, including medical images. 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 images authentication using methods, including techniques like Haar Transform, Histogram Shifting, Arnold’s Cat Map. The methods aim to embed an imperceptible watermark into images, which can later be extracted to verify the authenticity and integrity of the images.

This project demonstrates a reversible data hiding technique for image authentication. It combines Histogram Shifting with Arnold's Cat Map to embed watermarks securely without significant image degradation.

• Watermark embedding & extraction through reversible data hiding.
• Histogram Shifting for imperceptible watermarking.
• Arnold's Cat Map scrambling for enhanced security.
• Performance metrics: PSNR, SSIM, and NCC.
• Resistance to common image processing attacks.