This project aims to develop a tool to detect spatial forgery detection in the videos based on a dataset composed of modified videos for forensic investigation. We will create a new data set of forged videos, primary purpose of developing and designing this new video library is for us
Spatial video forgery detection
This project aims to develop a tool to detect spatial forgery detection in the videos based on a dataset composed of modified videos for forensic investigation. We will create a new data set of forged videos, primary purpose of developing and designing this new video library is for usage in video forensics, which can be consciously associated with reliable verification using dynamic and static camera recognition and developing the ground truth of the dataset. To the best of our knowledge, there exists no similar library among the research community. Footage from digital camcorders and smart phones will be included as well. Then we will use this data set to develop a tool for spatial forgery detection, it will take video as input in any format and as a output it will tell whether the video is forged or not, if it is then which technique is used to temper that video. Researchers will greatly benefit from such a library, as they will be provided with a general demonstration video to build a standard for their forensics algorithms.
The above developed dataset will be used to develop the tool that will detect the video forgery. Basically it will be based on Artificial intelligence, implementation steps are given below:
(1) Input
First or all we will give a video as a input in the tool and it be stored in the database for processing and future learning.
(2) Frame extraction
In the second step we will extract the frames of the video and store them on a specific location so that each frame will be processed
(3) Frame comparison
Now the extract frames will be compare based on some decision models(DOCFs) to find whether any of them frame is tampered on not
(4) Generate output
Based on the above results the output will generate if any frame is found tampered then the video will be regard as tempered
The whole process is shown in the following figure:-

Following tool will be used to develop the tool :-
1) Matlab
2) Python
3) Adobe premiere Pro CC
4) PyCharm(IDE)
1) The tool will be able to take any type of video in any type of format
2) It will separate all frame in the videos and examine individually
3) Support Vector Machine or other models will be used to detect whether the pair of consecutive frames is forged. If at least one pair of consecutive frames is detected as forged, the video segment is predicted as forged and the forged frames are localized.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Nikkon D5200 camera | Equipment | 1 | 38000 | 38000 |
| IP cam | Equipment | 1 | 5000 | 5000 |
| Robotic camera | Equipment | 1 | 5000 | 5000 |
| Tripod | Equipment | 1 | 3000 | 3000 |
| Android Mobile | Equipment | 1 | 18000 | 18000 |
| Printing,Storage etc | Miscellaneous | 1 | 4500 | 4500 |
| Software Licence | Miscellaneous | 1 | 5000 | 5000 |
| Total in (Rs) | 78500 |
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