University of Bahrain
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Detection Tampering in Digital Video in Frequency Domain using DCT with Halftone

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dc.contributor.author H. Alwan, Wafaa
dc.contributor.author M. Alturfi, Sabah
dc.date.accessioned 2024-02-02T17:36:34Z
dc.date.available 2024-02-02T17:36:34Z
dc.date.issued 2024-02-05
dc.identifier.issn 2210-142X
dc.identifier.uri https://journal.uob.edu.bh:443/handle/123456789/5409
dc.description.abstract In recent years, the rapid technological development and the emergence of mobile devices, cameras, etc., in addition to the availability of video production, editing, and formatting programs, made it easy to edit, manipulate, and fake or tamper video. As they know that pictures or videos give more information than texts; Video is a very important medium for transferring information from one place to another. One of the important types of evidence in road accidents and theft crimes. Moreover, when forensic analysis is essential for any video, the availability of origin video may be rare therefore the forensic experts must establish decisions based on the present video (under surveillance) and decide if this video is fake (tampered) or not fake. There are multiple methods to tamper video, including active and blind passive methods. In this research, we tried to combine the behavior of active methods in the process of embedding the halftone current frame of video in the DCT Coefficients of next frame of the same video with the behavior of passive methods by comparing the information embedded after extracting with the information of the current frame to determine whether there is a fake in the video or not and which frame contains tamper. The experimental results of the submitted method showed a huge level of success in locating frames in which falsification or tampering occurred through copying, deletion or insertion, or even if copy-move regions. Also, in proposed method we attempted to post-processing the fake frames using the information included in the subsequent frame, if it is not faked. Finally, the original video, the embedded halftone video, and the tamper (fake) video after post processing were compared using PSNR and SSIM similarity scales. At last, the accuracy and precision scores of tampered and non tampered frames are computed. en_US
dc.language.iso en en_US
dc.publisher University Of Bahrain en_US
dc.subject Video tampering en_US
dc.subject DCT transform en_US
dc.subject Halftone algorithm en_US
dc.subject PSNR- SSIM Similarity measure en_US
dc.subject Gaussian filter en_US
dc.title Detection Tampering in Digital Video in Frequency Domain using DCT with Halftone en_US
dc.type Article en_US
dc.identifier.doi http://dx.doi.org/10.12785/ijcds/150163
dc.volume 15 en_US
dc.issue 1 en_US
dc.pagestart 879 en_US
dc.pageend 887 en_US
dc.contributor.authorcountry Iraq en_US
dc.contributor.authoraffiliation College of Computer Science Information Technology, University of Kerbala, Kerbala en_US
dc.contributor.authoraffiliation College of law, University of Kerbala, Kerbala en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US


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