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Computer Science and Information Technologies
Article . 2023 . Peer-reviewed
License: CC BY SA
Data sources: Crossref
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ZENODO
Article . 2023
License: CC BY
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Key-frame extraction based video watermarking using speeded up robust features and discrete cosine transform

Authors: Kapre Bhagyashri S.; Rajurkar Archana M.;

Key-frame extraction based video watermarking using speeded up robust features and discrete cosine transform

Abstract

Due to advancements in the internet and multimedia technologies, unauthorised users can easily modify video content. As a result, video authentication has been established as a viable solution for ensuring multimedia security. We propose a key-frame based video watermarking scheme based on discrete cosine transform (DCT). First, the Pearson correlation coefficient (PCC) is used to detect the shot boundaries of the input video. To reduce the difficulties created by traditional video watermarking systems; an entropy measure is employed to detect key-frames from input video. Traditional schemes entail embedding the entire watermark into all frames of the video, which is inefficient and time-consuming. To improve the security, robustness, and imperceptibility of the proposed video watermarking scheme, speeded up robust feature points are extracted from each key-frame of the shot and used as reference points for embedding and detection of watermark. The embedded watermark is extracted blindly without using the original data during the extraction process. The results of the experiments reveal that the proposed technique effectively detects shot boundaries under a variety of camera operations and outperforms in terms of imperceptibility and resilience.

Keywords

Discrete cosine transform speed-up robust features, Entropy, Watermark, Pearson correlation coefficient, Extraction, Embedding

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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