A Robust Image Watermarking Algorithm Based on Content Authentication and Intelligent Optimization

Aiming at some shortcomings of current digital watermarking algorithms, a color image double watermarking algorithm based on content authentication and machine learning is proposed in this paper. Firstly, the algorithm combines discrete wavelet transform (DWT) and discrete cosine transform (DCT), and embeds the watermark through singular value decomposition (SVD) modulation. Secondly, using the learning and classification characteristics of Support Vector Machine (SVM), the watermark detection model is obtained through training a large number of data, and finally the robust watermark is extracted automatically. In order to realize content authentication and tamper location, the algorithm embeds a fragile watermark at the same time, and uses the relationship between the high-frequency coefficients of wavelet transform to embed and extract the watermark. Through the simulation results and data analysis, the proposed double watermarking algorithm not only realizes the intelligent watermark extraction process, but also can accurately locate malicious tampering while maintaining strong robustness.