journal article·2023Open access

New Fragile Watermarking Technique to Identify Inserted Video Objects Using H.264 and Color Features

Raheem Ogla, Eman Shakar Mahmood, Rasha I. Ahmed, Abdul Monem S. Rahma

Computers, Materials & Continua· Volume 76· Issue 3

Abstract

The transmission of video content over a network raises various issues relating to copyright authenticity, ethics, legality, and privacy. The protection of copyrighted video content is a significant issue in the video industry, and it is essential to find effective solutions to prevent tampering and modification of digital video content during its transmission through digital media. However, there are still many unresolved challenges. This paper aims to address those challenges by proposing a new technique for detecting moving objects in digital videos, which can help prove the credibility of video content by detecting any fake objects inserted by hackers. The proposed technique involves using two methods, the H.264 and the extraction color features methods, to embed and extract watermarks in video frames. The study tested the performance of the system against various attacks and found it to be robust. The evaluation was done using different metrics such as Peak-Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Structural Similarity Index Measure (SSIM), Bit Correction Ratio (BCR), and Normalized Correlation. The accuracy of identifying moving objects was high, ranging from 96.3% to 98.7%. The system was also able to embed a fragile watermark with a success rate of over 93.65% and had an average capacity of hiding of 78.67. The reconstructed video frames had high quality with a PSNR of at least 65.45 dB and SSIM of over 0.97, making them imperceptible to the human eye. The system also had an acceptable average time difference (T = 1.227/s) compared with other state-of-the-art methods.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Steganography and Watermarking Techniques · Digital Media Forensic Detection · Chaos-based Image/Signal Encryption

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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