Method and device for determining black margin position information of video

Abstract

The invention is to provide a method and device for determining black margin position information of a video. The method specifically comprises the following steps: cutting out at least one original video image from a video to be processed; carrying out boundary sampling processing on the original video image to obtain a boundary sampling image corresponding to the video; determining first black margin position information corresponding to the boundary sampling image; and determining second black margin position information corresponding to the video according to the first black margin position information. Compared with the prior art, the method carries out boundary sampling processing on the original video image captured from the video to obtain the corresponding boundary sampling image, so that the second black margin position information corresponding to the video is determined according to the determined first black margin position information of the boundary sampling image; and the black margin position of the video is determined by determining the black margin position of the boundary sampling image, so that time complexity of the processing is reduced, detection efficiency and detection accuracy of the black margin position are improved, and detection robustness is enhanced.

Description

technical field [0001] The present invention relates to the field of video technology, in particular to a technology for determining black border position information of a video. Background technique [0002] In the process of video processing, black borders are often added to the video image to fit the existing screen basic picture length and width dimensions, such as the standard aspect ratio of 4:3 and the wide screen aspect ratio of 16:9, and these black borders Not only is it meaningless, but sometimes it even covers the picture content in the video image, which reduces the user's video viewing experience. In the prior art, the threshold detection method is usually used to determine the black edge. In this method, the pixels whose pixel values ​​exceed the predetermined threshold are regarded as non-black pixels. By counting the non-black pixels of each row / column, when the non-black pixels are less than the predetermined threshold If the row / column is judged to be a b...

AI Technical Summary

Problems solved by technology

[0002] In the process of video processing, black borders are often added to the video image to fit the existing screen basic picture length and width dimensions, such as the standard aspect ratio of 4:3 and the wide screen aspect ratio of 16:9, and these black borders Not only has no practical significance, but sometimes even covers the content of the video image, which reduces the user's video viewing experience

In the prior art, the threshold detection method is usually used to determine the black edge. In this method, the pixels whose pixel values ​​exceed the predetermined threshold are regarded as non-black pixels. By counting the non-black pixels of each row / column, when the non-black pixels are less than the predetermined threshold If the row / column is judged to be a black border, otherwise it is considered to be a non-black border. Since the black border is not a definite value, but within a certain range, when the threshold is set too high / too low, the threshold detection method will cause Inaccurate detection of black edges, for example, when the threshold is too high, gray pixels will be treated as black dots, and when the threshold is too low, too many non-black dots will be detected, and the whole page will be scanned image, detection efficiency is low

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