Digital image forgery detection
Digital image forgery has become a widespread phenomenon in today’s society. Digital images are easy to manipulate and edit due to availability of powerful image processing and editing software. It is possible to add or remove important features from an image without leaving any obvious traces of ta...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2011
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| Online Access: | http://hdl.handle.net/10356/43902 |
| _version_ | 1826120443335016448 |
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| author | Tay, Qinyuan. |
| author2 | Sudha Natarajan |
| author_facet | Sudha Natarajan Tay, Qinyuan. |
| author_sort | Tay, Qinyuan. |
| collection | NTU |
| description | Digital image forgery has become a widespread phenomenon in today’s society. Digital images are easy to manipulate and edit due to availability of powerful image processing and editing software. It is possible to add or remove important features from an image without leaving any obvious traces of tampering. As digital cameras and video cameras replace their analog counterparts, there is a pressing need for authenticating digital images, validating their content and detection of forgeries.
The purpose of the project is to conduct an experimental investigation of using SIFT and SURF techniques in digital image detection forgery. The author focuses on the detection of a common digital forgery called the copy-move forgery. A part of the image is replicated and pasted onto a part in the image to remove traces of an important image feature. In this project, the author implements SIFT and SURF techniques to detect the forged part even when the image is altered. The performance of the implementations is described in the later parts of the project. |
| first_indexed | 2024-10-01T05:16:50Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/43902 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:16:50Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | ntu-10356/439022023-03-03T20:43:49Z Digital image forgery detection Tay, Qinyuan. Sudha Natarajan School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Digital image forgery has become a widespread phenomenon in today’s society. Digital images are easy to manipulate and edit due to availability of powerful image processing and editing software. It is possible to add or remove important features from an image without leaving any obvious traces of tampering. As digital cameras and video cameras replace their analog counterparts, there is a pressing need for authenticating digital images, validating their content and detection of forgeries. The purpose of the project is to conduct an experimental investigation of using SIFT and SURF techniques in digital image detection forgery. The author focuses on the detection of a common digital forgery called the copy-move forgery. A part of the image is replicated and pasted onto a part in the image to remove traces of an important image feature. In this project, the author implements SIFT and SURF techniques to detect the forged part even when the image is altered. The performance of the implementations is described in the later parts of the project. Bachelor of Engineering (Computer Engineering) 2011-05-12T07:28:31Z 2011-05-12T07:28:31Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/43902 en Nanyang Technological University 49 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Tay, Qinyuan. Digital image forgery detection |
| title | Digital image forgery detection |
| title_full | Digital image forgery detection |
| title_fullStr | Digital image forgery detection |
| title_full_unstemmed | Digital image forgery detection |
| title_short | Digital image forgery detection |
| title_sort | digital image forgery detection |
| topic | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision |
| url | http://hdl.handle.net/10356/43902 |
| work_keys_str_mv | AT tayqinyuan digitalimageforgerydetection |