A Developed Technique for Digital Video Watermarking Using the Energy Values of Selective Blocks
Abstract
Fast internet speeds have made video streaming a common part of our everyday lives. As videos become increasingly important for sharing information, there are growing concerns about protecting copyrighted content. This highlights some limitations of current digital video watermarking techniques, including limited robustness, blurriness, and increased complexity. There is a clear need to adopt better tools and advanced technologies to address issues such as video tampering and unauthorized access. Our work introduces an effective, user-friendly technique to safeguard digital videos against these risks, offering a fresh approach to addressing this research gap. We propose a method that measures the energy of pixels within each frame's blocks to decide where to embed the watermark, ensuring minimal distortion by carefully adjusting parameters. This technique segments videos into frames and divides each frame into evenly sized blocks, without compromising the video's quality. Designed to withstand typical video processing tasks, our approach is innovative in embedding watermarks directly into the video content, making it resilient against attacks and protecting intellectual property, copyrights, and digital assets from tampering, misuse, copying, and forgery. We used several evaluation measures—such as block energy calculations, PSNR, MSE, SSIM, BER, NC, BCR, and performance metrics like FPR, FNR, TPR, and accuracy—to assess the watermark's robustness and imperceptibility. The results are promising: our method improves robustness and visual quality, with average PSNR values of 52.34%-53.98% and SSIM scores of 0.986-0.996%, marking a notable improvement over existing techniques. The embedding process is efficient, taking around 0.48521 seconds on average. Overall, this study offers a practical and reliable way to protect digital videos from unauthorized access and tampering.
Fields of Study & Subjects
Advanced Steganography and Watermarking Techniques
Image and Video Quality Assessment
Digital Media Forensic Detection
Publication details
- Journal / source
- JOIV International Journal on Informatics Visualization
- Volume
- 10
- Issue
- 1
- Pages
- 390–390
- Publication date
- 30 January 2026
- Language
- EN