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<p>This paper introduces a robust and efficient digital image watermarking technique designed for precise tamper detection and localization. The proposed approach integrates Singular Value Decomposition (SVD) and QR decomposition to generate two distinct authentication bits (Au1 and Au2), ensuring enhanced imperceptibility and security. These authentication bits are embedded into the cover image (CI) using a novel Scale-based Embedding Factor Quantization Index Modulation (SEF-QIM) technique. This embedding strategy guarantees resilience against various challenges, including geometric distortions, compression, and noise. Comprehensive experimental evaluations conducted on grayscale images demonstrate exceptional imperceptibility, achieving peak signal-to-noise ratio (PSNR) values exceeding 54&#xa0;dB and 52&#xa0;dB for scaling factors of 2 and 4, respectively. Additionally, the proposed method exhibits strong robustness against common attacks such as Gaussian noise, cropping, and rotation. The computational efficiency of the scheme ensures reduced time complexity for both embedding and extraction processes, making it a reliable and secure solution for image authentication in high-integrity digital media applications.</p>

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SEF-QIM: Scale-based Embedding Factor Quantization Index Modulation Image Watermarking for Tamper Detection and Localization

  • 期刊论文

  • 发表日期：

    2026年7月1日

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  • Swapnaneel Dhar,
  • Riyanka Manna,
  • Khaldi Amine,
  • Aditya Kumar Sahu

摘要

This paper introduces a robust and efficient digital image watermarking technique designed for precise tamper detection and localization. The proposed approach integrates Singular Value Decomposition (SVD) and QR decomposition to generate two distinct authentication bits (Au1 and Au2), ensuring enhanced imperceptibility and security. These authentication bits are embedded into the cover image (CI) using a novel Scale-based Embedding Factor Quantization Index Modulation (SEF-QIM) technique. This embedding strategy guarantees resilience against various challenges, including geometric distortions, compression, and noise. Comprehensive experimental evaluations conducted on grayscale images demonstrate exceptional imperceptibility, achieving peak signal-to-noise ratio (PSNR) values exceeding 54 dB and 52 dB for scaling factors of 2 and 4, respectively. Additionally, the proposed method exhibits strong robustness against common attacks such as Gaussian noise, cropping, and rotation. The computational efficiency of the scheme ensures reduced time complexity for both embedding and extraction processes, making it a reliable and secure solution for image authentication in high-integrity digital media applications.