A comprehensive survey on state-of-the-art video forgery detection techniques

被引:6
|
作者
Mohiuddin, Sk [1 ]
Malakar, Samir [1 ]
Kumar, Munish [2 ]
Sarkar, Ram [3 ]
机构
[1] Asutosh Coll, Dept Comp Sci, Kolkata 700026, India
[2] Maharaja Ranjit Singh Punjab Tech Univ, Dept Computat Sci, Bathinda 151001, India
[3] Jadavpur Univ, Dept Comp Sci & Engn, Kolkata 700032, India
关键词
Video forgery detection; Passive approach; Active approach; Copy-move video forgery; Deepfake; Surveillance video; Survey; DETECTION ALGORITHM; FRAME DELETION; TAMPERING DETECTION; DOUBLE COMPRESSION; UPSCALE-CROP; LOCALIZATION; CLASSIFICATION;
D O I
10.1007/s11042-023-14870-8
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Video plays a key role in carrying authenticity, especially in the surveillance system, medical field, court evidence, journalism, and social media among others. However, nowadays the trust in videos is decreasing day by day due to the forgery of the videos made by easily accessible video editing tools. Hence, a thrust for finding a robust solution to the problem of video forgery detection arises. As a result, researchers around the world are indulging themselves to come up with various methods for the said problem. In this article, we have comprehensively discussed many such initiatives made by researchers across the globe, keeping the focus on recent trends. In addition to this, we have also covered a wide range of forgery detection techniques that follow either an active or a passive approach, while the state-of-the-art surveys made so far on this research topic include only a few specific cases. In this article, we have described some recent technologies that are used in video forging, made a summary of the performances (provided categorically) of all the techniques discussed here, and briefed the available datasets. Finally, we have concluded this survey by clearly mentioning some future directions of the video forgery detection research based on a thorough review of existing techniques.
引用
收藏
页码:33499 / 33539
页数:41
相关论文
共 50 条
  • [1] A comprehensive survey on state-of-the-art video forgery detection techniques
    Sk Mohiuddin
    Samir Malakar
    Munish Kumar
    Ram Sarkar
    Multimedia Tools and Applications, 2023, 82 : 33499 - 33539
  • [2] A comprehensive survey of specularity detection: state-of-the-art techniques and breakthroughs
    Fengze Li
    Jieming Ma
    Hai-Ning Liang
    Zhongbei Tian
    Zhijing Wu
    Tianxi Wen
    Dawei Liu
    Artificial Intelligence Review, 58 (7)
  • [3] A comprehensive survey on passive techniques for digital video forgery detection
    Shelke, Nitin Arvind
    Kasana, Singara Singh
    MULTIMEDIA TOOLS AND APPLICATIONS, 2021, 80 (04) : 6247 - 6310
  • [4] A comprehensive survey on passive techniques for digital video forgery detection
    Nitin Arvind Shelke
    Singara Singh Kasana
    Multimedia Tools and Applications, 2021, 80 : 6247 - 6310
  • [5] A Survey on State-of-the-Art Drowsiness Detection Techniques
    Ramzan, Muhammad
    Khan, Hikmat Ullah
    Awan, Shahid Mahmood
    Ismail, Amina
    Ilyas, Mahwish
    Mahmood, Ahsan
    IEEE ACCESS, 2019, 7 : 61904 - 61919
  • [6] State-of-the-art techniques for passive image forgery detection: a brief review
    Kaur, Simranjot
    Sharma, Nonita
    INTERNATIONAL JOURNAL OF ELECTRONIC SECURITY AND DIGITAL FORENSICS, 2022, 14 (05) : 456 - 473
  • [7] HUMAN DETECTION IN VIDEO AND IMAGES - A STATE-OF-THE-ART SURVEY
    Walia, Gurjit Singh
    Kapoor, Rajiv
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2014, 28 (03)
  • [8] Passive Video Forgery Detection Techniques: A Survey
    Wahab, Ainuddin Wahid Abdul
    Bagiwa, Mustapha Aminu
    Idris, Mohd Yamani Idna
    Khan, Suleman
    Razak, Zaidi
    Ariffin, Muhammad Rezal Kamel
    2014 10TH INTERNATIONAL CONFERENCE ON INFORMATION ASSURANCE AND SECURITY (IAS), 2014, : 29 - 34
  • [9] State-of-the-art and future challenges in video scene detection: a survey
    Manfred Del Fabro
    Laszlo Böszörmenyi
    Multimedia Systems, 2013, 19 : 427 - 454
  • [10] State-of-the-art and future challenges in video scene detection: a survey
    Del Fabro, Manfred
    Boeszoermenyi, Laszlo
    MULTIMEDIA SYSTEMS, 2013, 19 (05) : 427 - 454