Scholarlink

<p>As images are integral to many sectors in the digital age, it is essential to ensure their authenticity and integrity. However, the ease of digital image creation and sharing also exposes them to manipulation and misrepresentation, heightening concerns about privacy and misinformation. The process of recapturing, a prevalent anti-forensic technique, poses challenges to tampering detection methods, necessitating effective countermeasures to uphold image credibility. Monitor-screenshots, facilitated by the simplicity of capturing screenshots of Original images displayed on monitors, pose unique challenges in source identification. Addressing this, we propose a novel approach to unveil the screen fingerprint, capturing distinctive irregularities associated with blur exist in Monitor-screenshots for accurate source identification. Leveraging image registration, difference image masking, and sophisticated feature extraction techniques, our method enables precise identification of specific screens, enhancing the authentication of digital content. By scrutinizing screen-specific characteristics and artifacts left during recapture, proposed model can verify the claimed origin of Screenshots, tested on a Screenshot dataset using SVM classifier, offers a robust framework to authenticate digital content and trace its source with precision and reliability, mitigating risks associated with image manipulation and misrepresentation in the digital domain.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Source screen identification using difference image mask obtained from images recaptured through screenshots based on spatial rich features

  • 期刊论文

  • 发表日期：

    2025年2月28日

查看全文
  • Areesha Anjum,
  • Saiful Islam,
  • Mahreen Saleem,
  • Nadia Siddiqui

摘要

As images are integral to many sectors in the digital age, it is essential to ensure their authenticity and integrity. However, the ease of digital image creation and sharing also exposes them to manipulation and misrepresentation, heightening concerns about privacy and misinformation. The process of recapturing, a prevalent anti-forensic technique, poses challenges to tampering detection methods, necessitating effective countermeasures to uphold image credibility. Monitor-screenshots, facilitated by the simplicity of capturing screenshots of Original images displayed on monitors, pose unique challenges in source identification. Addressing this, we propose a novel approach to unveil the screen fingerprint, capturing distinctive irregularities associated with blur exist in Monitor-screenshots for accurate source identification. Leveraging image registration, difference image masking, and sophisticated feature extraction techniques, our method enables precise identification of specific screens, enhancing the authentication of digital content. By scrutinizing screen-specific characteristics and artifacts left during recapture, proposed model can verify the claimed origin of Screenshots, tested on a Screenshot dataset using SVM classifier, offers a robust framework to authenticate digital content and trace its source with precision and reliability, mitigating risks associated with image manipulation and misrepresentation in the digital domain.