Video interframe forgery detection: Classification, technique & new dataset

被引:5
作者
Sharma, Himani [1 ]
Kanwal, Navdeep [1 ]
机构
[1] Punjabi Univ Patiala, Dept Comp Sci & Engn, Patiala, Punjab, India
关键词
Video forgery detection; interframe forgery; frame duplication; Hu moments; Dataset library; LOCALIZATION; SCHEME;
D O I
10.3233/JCS-200105
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Multimedia communication as well as other related innovations are gaining tremendous growth in the modern technological era. Even though digital content has traditionally proved to be a piece of legitimate evidence. But the latest technologies have lessened this trust, as a variety of video editing tools have been developed to modify the original video. Therefore, in order to resolve this problem, a new technique has been proposed for the detection of duplicate video sequences. The present paper utilizes gray values to extract Hu moment features in the current frame. These features are further used for classification of video as authentic or forged. Afterwards there was also need to validate the proposed technique using training and test dataset. But the scarcity of training and test datasets, however, is indeed one of the key problems to validate the effectiveness of video tampering detection techniques. In this perspective, the Video Forensics Library for Frame Duplication (VLFD) dataset has been introduced for frame duplication detection purposes. The proposed dataset is made of 210 native videos, in Ultra-HD and Full-HD resolution, captured with different cameras. Every video is 6 to 15 seconds in length and runs at 30 frames per second. All the recordings have been acquired in three different scenarios (indoor, outdoor, nature) and in landscape mode(s). VLFD includes both authentic and manipulated video files. This dataset has been created as an initial repository for manipulated video and enhanced with new features and new techniques in future.
引用
收藏
页码:531 / 550
页数:20
相关论文
共 55 条
  • [21] Digital image splicing detection technique using optimal threshold based local ternary pattern
    Kanwal, Navdeep
    Girdhar, Akshay
    Kaur, Lakhwinder
    Bhullar, Jaskaran S.
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (19-20) : 12829 - 12846
  • [22] Kaur C., 2019, Stat. Optim. Inf. Comput, V7, P486, DOI DOI 10.19139/SOIC.V7I2.542
  • [23] Li L., 2012, INT WORKSH DIG WAT, P242
  • [24] Liao SY, 2013, 2013 6TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP), VOLS 1-3, P864, DOI 10.1109/CISP.2013.6745286
  • [25] Lin C. Y., 1998, P MULT SEC WORKSH AC, P49
  • [26] A passive approach for effective detection and localization of region-level video forgery with spatio-temporal coherence analysis
    Lin, Cheng-Shian
    Tsay, Jyh-Jong
    [J]. DIGITAL INVESTIGATION, 2014, 11 (02) : 120 - 140
  • [27] DETECTION OF FRAME DUPLICATION FORGERY IN VIDEOS BASED ON SPATIAL AND TEMPORAL ANALYSIS
    Lin, Guo-Shiang
    Chang, Jie-Fan
    [J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2012, 26 (07)
  • [28] Liu YQ, 2017, MULTIMEDIA SYST, V23, P223, DOI [10.1007/s00530-015-0478-1, 10.1007/s00530-015-0461-x]
  • [29] Mahmood T., 2016, Int. J. Comput. Sci. Inf. Secur, V14, P156
  • [30] Copy-Move Forgery Detection Technique for Forensic Analysis in Digital Images
    Mahmood, Toqeer
    Nawaz, Tabassam
    Irtaza, Aun
    Ashraf, Rehan
    Shah, Mohsin
    Mahmood, Muhammad Tariq
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2016, 2016