Digital Image Watermarking via Adaptive Logo Texturization

Area of Science:

• Digital Image Processing
• Computer Vision
• Information Security

Background:

• Grayscale logo watermarking is established for visual authentication.
• Invisible watermarking faces challenges in imperceptibility and robustness against attacks.

Purpose of the Study:

• To develop an invisible grayscale logo watermarking algorithm.
• To enhance robustness and imperceptibility of watermarks.

Main Methods:

• The algorithm uses adaptive texturization by separating host images into textured and poorly textured regions.
• Logos are transformed into visually similar textures using Arnold transform and lossless rotation, guided by visual texture similarity models.
• A wavelet-based embedding scheme is employed, followed by a multistep extraction with affine parameter estimation.

Main Results:

• The proposed algorithm demonstrates superior overall performance compared to competing methods.
• Testing across various logos, host images, and attacks validates the algorithm's effectiveness.

Conclusions:

• The adaptive texturization approach effectively addresses challenges in invisible grayscale logo watermarking.
• The method offers a robust and imperceptible solution for digital image watermarking.