Abstract: Watermark embedding intensity is a key issue in data watermarking research and closely related to the robustness and imperceptibility of watermarking. This paper proposes a watermarking algorithm of adaptive embedding intensity based on SVR model for image data. In terms of image features， the LBP operator of the image and the low frequency coefficients of the wavelet transform are selected. The appropriate watermark embedding intensity is determined according to the SSIM index. Hence， the training dataset is generated and the SVR model is trained. In the process of watermark embedding， the watermark is encrypted first， then the DCT transform is applied to the image sub-blocks and the trained SVR model is used in watermark embedding to adjust the embedding intensity. Similarly， the extraction of the watermark can be performed in an inverse procedure based on the key and SVR model. The experimental results show that the proposed watermarking algorithm can perform adaptive watermark embedding and extraction on images while ensuring the image quality and watermark invisibility， and also has good robustness to adding noise， compression， image clipping and other types of attack.

Key words: SVR, intensity of watermark, LBP operator, wavelet transform, Arnold transformation