In this paper, we propose a robust block classification based semi-blind video watermarking algorithm using visual cryptography and SURF (Speed-Up Robust Features) features to enhance the robustness, stability, imperceptibility and real-time performance. A method of selecting the best frames in each shot and the best regions or blocks within best frames is proposed to avoid employing frame–by-frame method for generating owner’s share in order to enhance robustness as well as reducing time complexity. In our method, Owner’s share is generated using the classification of selected robust blocks within the chosen frames along with corresponding watermark information. In extraction process, the SURF features are employed to match the feature points of selected frames with all frames to detect selected frames. Moreover, we resynchronize the embedded regions from distorted video to original sequence using SURF feature points matching. Afterwards, based on these matched feature points, rotation and scaling parameters are estimated next, selected blocks are retrieved using side information being stored eventually, watermark information is reconstructed successfully. Selecting Best frames, best regions, and employing surf features make our method to be highly robust against various kinds of attacks including image processing attacks, geometrical attacks and temporal attacks. Experimental results confirm the superiority of our scheme in case of being applicable in the real world, enhancing robustness and exploiting idea imperceptibility, over previous related methods.
