基于关键帧提取与DBSCAN的视频内容篡改识别技术

doi:10.13229/j.cnki.jdxbgxb.20241261

摘要/Abstract

摘要：

针对篡改视频内容审查和筛选导致大量人力资源消耗问题，本文提出了一种识别视频篡改内容的技术。首先，该技术通过计算帧间差异提取关键帧；其次，通过对关键帧与原始帧进行差值分析获取篡改位置；再次，基于位置关联和语义聚合现象，利用密度聚类算法（DBSCAN）算法解决因篡改位置和内容结构的随机性造成的位置分散和语义离散问题；最后，通过光学字符识别技术解析篡改的具体内容。本文方法实现了视频篡改内容的时空定位和内容识别，为公共安全、传媒、商务等领域的视频内容检测提供了坚实的技术基础。

关键词: 关键帧抽取, SSIM, DBSCAN, 形态学变换, 光学字符识别

Abstract:

To solve the problem of a large amount of human resource consumption caused by tampering with video content review and screening， a technique for identifying tampered content in videos is proposed in this paper. First， key frames are extracted by calculating inter-frame differences. Then， the locations of tampering are determined through differential analysis between the key frames and the original frames. Subsequently， based on the phenomenon of location association and semantic aggregation， the problems of location dispersion and semantic dispersion are solved by the DBSCAN algorithm， which is caused by the randomness of tampering with location and content structure. Finally， optical character recognition （OCR） technology is applied to decipher the specific content that has been altered. Spatio-temporal position and content identification of tampered video content are achieved by the proposed method， providing a solid technical foundation for video content inspection in fields such as public safety， media， and business.

Key words: keyframe extraction, SSIM, DBSCAN, morphological transformation, optical character recognition

中图分类号:

TP309.2

任飞. 基于关键帧提取与DBSCAN的视频内容篡改识别技术[J]. 吉林大学学报(工学版), 2026, 56(2): 555-563.

Fei REN. Video content tampering identification technology based on key frame extraction and DBSCAN[J]. Journal of Jilin University(Engineering and Technology Edition), 2026, 56(2): 555-563.

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方法	正确检测	误检测	准确率/%	召回率/%	检测时间/min
本文	1 630	165	96.55	90.21	56.84
光流法	2 419	1 701	65.12	54.20	171.67
MSSIM商	3 103	869	91.87	74.25	185.36
聚类法	2 521	226	93.33	91.60	68.68