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author:

Chen, Yan (Chen, Yan.) [1] | Yang, Zhongliao (Yang, Zhongliao.) [2] | Dong, Chen (Dong, Chen.) [3] (Scholars:董晨) | Lin, Hui (Lin, Hui.) [4] | Chen, Zhenyi (Chen, Zhenyi.) [5]

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Abstract:

The rise of the short-form video industry marks a revolutionary change in the digital media landscape. This has opened up new opportunities for content distribution and creation but has also brought about several challenges, one of which is the difficulty of effectively protecting video copyrights. In the industrial sector, for example, the industrial digital design, manufacturing, and production process often generate a large amount of video data. If these videos are stolen, copied, or tampered with by unauthorized third parties, infringement issues can arise. To effectively monitor and protect the video copyrights of users or enterprises, this paper proposes a lightweight video clip fast matching (KMP-FVFM) algorithm. The algorithm utilizes the idea of Knuth-Morris-Pratt (KMP) algorithm, which takes into account the inter-frame fragment relationship of the query video to improve the video matching speed. At the same time, the duplicate segment locations are pinpointed in the original video. This paper also implements a plain method for video fragment matching, and the experimental results show that KMP-FVFM can effectively improve the efficiency of video fragment matching. © 2023 IEEE.

Keyword:

Copyrights Digital storage

Community:

  • [ 1 ] [Chen, Yan]College of Computer and Data Science, Fuzhou University, Fuzhou; 350108, China
  • [ 2 ] [Yang, Zhongliao]College of Computer and Data Science, Fuzhou University, Fuzhou; 350108, China
  • [ 3 ] [Dong, Chen]College of Computer and Data Science, Fuzhou University, Fuzhou; 350108, China
  • [ 4 ] [Lin, Hui]College of Computer and Cyber Security, Fujian Normal University, Fuzhou; 350007, China
  • [ 5 ] [Chen, Zhenyi]University of South Florida, Department of Computer Science and Engineering, Tampa; FL; 33620, United States

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Year: 2023

Page: 220-227

Language: English

Cited Count:

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 1

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