Video forgery detection
Digital image and videos cannot be taken as authentic evidences, since their integrity is no longer trustworthy. Because of the uniqueness and peculiarities of video signals with respect to images, there are wider ranges of possible alterations that can be applied on video signals. So detection o...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/66170 |
| _version_ | 1811689789230940160 |
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| author | Mathai, Mareeta |
| author2 | Deepu Rajan |
| author_facet | Deepu Rajan Mathai, Mareeta |
| author_sort | Mathai, Mareeta |
| collection | NTU |
| description | Digital image and videos cannot be taken as authentic evidences, since their
integrity is no longer trustworthy. Because of the uniqueness and peculiarities of
video signals with respect to images, there are wider ranges of possible alterations
that can be applied on video signals. So detection of video forgery has become a
critical requirement to ensure integrity of video data. We examined currently
available image and video forgery detection methods and introduced our own
methods. This thesis presents our efforts to understand and improve video forgery
detection methods. Firstly, a supervised image splicing detection method, which
makes use of statistical moment features, is extended to find forgery in videos. Its
limitations are discussed and a subset of those features is used for our next section
of unsupervised methods. An unsupervised video forgery detection method based
on suitable subset of statistical moment features and normalized cross correlation
factor is proposed. The location of duplicated block is also found using the
algorithm. Its advantages, limitations and comparisons with existing methods is
also given. Finally, a semi-supervised video forgery detection method, which is
based on feature similarity index, is also proposed. The index, primarily made for
image quality assessment, is used for finding duplication among the frames in a
video sequence. Experimental results for the three methods are discussed. Detailed
literature review and the possible future work on the related research area are also
discussed in the thesis. |
| first_indexed | 2024-10-01T05:53:41Z |
| format | Thesis |
| id | ntu-10356/66170 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:53:41Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | ntu-10356/661702023-03-04T00:29:17Z Video forgery detection Mathai, Mareeta Deepu Rajan Sabu Emmanuel School of Computer Engineering DRNTU::Engineering Digital image and videos cannot be taken as authentic evidences, since their integrity is no longer trustworthy. Because of the uniqueness and peculiarities of video signals with respect to images, there are wider ranges of possible alterations that can be applied on video signals. So detection of video forgery has become a critical requirement to ensure integrity of video data. We examined currently available image and video forgery detection methods and introduced our own methods. This thesis presents our efforts to understand and improve video forgery detection methods. Firstly, a supervised image splicing detection method, which makes use of statistical moment features, is extended to find forgery in videos. Its limitations are discussed and a subset of those features is used for our next section of unsupervised methods. An unsupervised video forgery detection method based on suitable subset of statistical moment features and normalized cross correlation factor is proposed. The location of duplicated block is also found using the algorithm. Its advantages, limitations and comparisons with existing methods is also given. Finally, a semi-supervised video forgery detection method, which is based on feature similarity index, is also proposed. The index, primarily made for image quality assessment, is used for finding duplication among the frames in a video sequence. Experimental results for the three methods are discussed. Detailed literature review and the possible future work on the related research area are also discussed in the thesis. Master of Engineering (SCE) 2016-03-14T04:12:47Z 2016-03-14T04:12:47Z 2016 Thesis http://hdl.handle.net/10356/66170 en application/pdf |
| spellingShingle | DRNTU::Engineering Mathai, Mareeta Video forgery detection |
| title | Video forgery detection |
| title_full | Video forgery detection |
| title_fullStr | Video forgery detection |
| title_full_unstemmed | Video forgery detection |
| title_short | Video forgery detection |
| title_sort | video forgery detection |
| topic | DRNTU::Engineering |
| url | http://hdl.handle.net/10356/66170 |
| work_keys_str_mv | AT mathaimareeta videoforgerydetection |