Adaptive embedding algorithm based on deep learning
The core algorithm of taatoo adopts the generative adversarial network of U-Net architecture, where the generator is responsible for analyzing the image texture features and determining the best embedding area (usually choosing the mid-frequency detail-rich area), and the discriminator continuously evaluates the difference in human eye perception. The technology achieves three major breakthroughs: (1) dynamic capacity adjustment, which automatically adjusts the amount of watermark data (0.3-3bit/pixel) according to the complexity of the image; (2) frequency-domain mask technology, which avoids blocking artifacts caused by embedding in smooth areas (e.g., the sky); and (3) color adaptation mechanism, which employs different embedding strategies in CMYK and RGB spaces.
Actual test data shows that the processed image is >0.98 in SSIM structural similarity index, and the professional reviewer can only recognize 6.7% images with watermarks in double-blind test. Compared to OpenCV's traditional LSB algorithm, taatoo's anti-detection performance is improved by 8 times, which is especially suitable for 4K/8K high-precision commercial image protection.
This answer comes from the articletaatoo: invisible watermarking tool to secure imagesThe
