Video forgery detection using HOG features and compression properties
In this paper, we propose a novel video forgery detection technique to detect the spatial and temporal copy paste tampering. It is a challenge to detect the spatial and temporal copy-paste tampering in videos as the forged patch may drastically vary in terms of size, compression rate and compression...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Online Access: | https://hdl.handle.net/10356/96284 http://hdl.handle.net/10220/12000 |
| _version_ | 1811693039660302336 |
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| author | Subramanyam, A. V. Emmanuel, Sabu |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Subramanyam, A. V. Emmanuel, Sabu |
| author_sort | Subramanyam, A. V. |
| collection | NTU |
| description | In this paper, we propose a novel video forgery detection technique to detect the spatial and temporal copy paste tampering. It is a challenge to detect the spatial and temporal copy-paste tampering in videos as the forged patch may drastically vary in terms of size, compression rate and compression type (I, B or P) or other changes such as scaling and filtering. In our proposed algorithm, the copy-paste forgery detection is based on Histogram of Oriented Gradients (HOG) feature matching and video compression properties. The benefit of using HOG features is that they are robust against various signal processing manipulations. The experimental results show that the forgery detection performance is very effective. We also compare our results against a popular copy-paste forgery detection algorithm. In addition, we analyze the experimental results for different forged patch sizes under varying degree of modifications such as compression, scaling and filtering. |
| first_indexed | 2024-10-01T06:45:21Z |
| format | Conference Paper |
| id | ntu-10356/96284 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:45:21Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/962842020-05-28T07:41:41Z Video forgery detection using HOG features and compression properties Subramanyam, A. V. Emmanuel, Sabu School of Computer Engineering IEEE International Workshop on Multimedia Signal Processing (14th : 2012 : Banff, Alberta, Canada) DRNTU::Engineering::Computer science and engineering In this paper, we propose a novel video forgery detection technique to detect the spatial and temporal copy paste tampering. It is a challenge to detect the spatial and temporal copy-paste tampering in videos as the forged patch may drastically vary in terms of size, compression rate and compression type (I, B or P) or other changes such as scaling and filtering. In our proposed algorithm, the copy-paste forgery detection is based on Histogram of Oriented Gradients (HOG) feature matching and video compression properties. The benefit of using HOG features is that they are robust against various signal processing manipulations. The experimental results show that the forgery detection performance is very effective. We also compare our results against a popular copy-paste forgery detection algorithm. In addition, we analyze the experimental results for different forged patch sizes under varying degree of modifications such as compression, scaling and filtering. 2013-07-23T01:53:57Z 2019-12-06T19:28:10Z 2013-07-23T01:53:57Z 2019-12-06T19:28:10Z 2012 2012 Conference Paper Subramanyam, A. V.,& Emmanuel, S. (2012). Video forgery detection using HOG features and compression properties. 2012 IEEE 14th International Workshop on Multimedia Signal Processing (MMSP). https://hdl.handle.net/10356/96284 http://hdl.handle.net/10220/12000 10.1109/MMSP.2012.6343421 en © 2012 IEEE. |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Subramanyam, A. V. Emmanuel, Sabu Video forgery detection using HOG features and compression properties |
| title | Video forgery detection using HOG features and compression properties |
| title_full | Video forgery detection using HOG features and compression properties |
| title_fullStr | Video forgery detection using HOG features and compression properties |
| title_full_unstemmed | Video forgery detection using HOG features and compression properties |
| title_short | Video forgery detection using HOG features and compression properties |
| title_sort | video forgery detection using hog features and compression properties |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/96284 http://hdl.handle.net/10220/12000 |
| work_keys_str_mv | AT subramanyamav videoforgerydetectionusinghogfeaturesandcompressionproperties AT emmanuelsabu videoforgerydetectionusinghogfeaturesandcompressionproperties |