A video watermark recognition method and its recognition device

Abstract

The present invention provides a video watermark recognition method and a recognition device thereof, wherein the recognition method includes: acquiring a video frame of a video, and selecting a video frame as a comparison video frame; frame as the current video frame; identify similar pixels according to the pixel values ​​of the same position of the current video frame and the comparison video frame; remove non-similar pixels except similar pixels in the current video frame, and Use the current video frame with non-similar pixels removed as a new comparison video frame; return to the above steps until the last frame of the current video frame of the video is compared; obtain adjacent pixels adjacent to similar pixels, according to similar pixels The watermark range in the video is obtained from the points and adjacent pixels; the watermark range is divided into blocks to obtain at least one watermark area divided into blocks. The beneficial effect of the present invention lies in: improving the identification speed of the watermark.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a video watermark recognition method and a recognition device thereof. Background technique [0002] With the rapid development of digital media technology and computer technology, digital media such as video can be spread rapidly through the Internet. In order to protect the copyright of the video, the watermark is usually embedded when the video is produced, and the video watermark is played simultaneously when the video is played. However, when the video is played, since the content of the video watermark and the original image of the video are compressed together, the watermark will be displayed while playing the original video. Therefore, a method for removing the watermark in the video is currently needed. [0003] In the prior art, the SIFT algorithm or neural network recognition algorithm is usually used to identify the watermark in the video, but the above-mentioned p...

AI Technical Summary

Problems solved by technology

[0004] First, the calculation speed is slow, and each calculation takes several minutes or even hours of calculation time, and the user cannot use other applications during this period, so it will bring a lot of inconvenience to the user;

[0005] Second, the complexity of the algorithm is high, so it needs to consume more computing resources, especially the deep learning technology needs to use dedicated GPU resources to accelerate the learning process;

[0006] Third, the scalability is insufficient. Technologies such as pattern recognition and deep learning need to prepare a large amount of training data in advance, and the training results and the selection of samples have a relatively strong correlation, so they can only be applied to limited types of scenarios.

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