State of the art in passive digital image forgery detection: copy-move image forgery
Authenticating digital images is increasingly becoming important because digital images carry important information and due to their use in different areas such as courts of law as essential pieces of evidence. Nowadays, authenticating digital images is difficult because manipulating them has become...
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| Format: | Article |
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Springer Verlag
2018
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| _version_ | 1796961318495846400 |
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| author | Sadeghi, Somayeh Dadkhah, Sajjad Jalab, Hamid Abdullah Mazzola, Giuseppe Uliyan, Diaa Mohammed |
| author_facet | Sadeghi, Somayeh Dadkhah, Sajjad Jalab, Hamid Abdullah Mazzola, Giuseppe Uliyan, Diaa Mohammed |
| author_sort | Sadeghi, Somayeh |
| collection | UM |
| description | Authenticating digital images is increasingly becoming important because digital images carry important information and due to their use in different areas such as courts of law as essential pieces of evidence. Nowadays, authenticating digital images is difficult because manipulating them has become easy as a result of powerful image processing software and human knowledge. The importance and relevance of digital image forensics has attracted various researchers to establish different techniques for detection in image forensics. The core category of image forensics is passive image forgery detection. One of the most important passive forgeries that affect the originality of the image is copy-move digital image forgery, which involves copying one part of the image onto another area of the same image. Various methods have been proposed to detect copy-move forgery that uses different types of transformations. The goal of this paper is to determine which copy-move forgery detection methods are best for different image attributes such as JPEG compression, scaling, rotation. The advantages and drawbacks of each method are also highlighted. Thus, the current state-of-the-art image forgery detection techniques are discussed along with their advantages and drawbacks. |
| first_indexed | 2024-03-06T05:52:27Z |
| format | Article |
| id | um.eprints-20842 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:52:27Z |
| publishDate | 2018 |
| publisher | Springer Verlag |
| record_format | dspace |
| spelling | um.eprints-208422019-04-09T03:03:19Z http://eprints.um.edu.my/20842/ State of the art in passive digital image forgery detection: copy-move image forgery Sadeghi, Somayeh Dadkhah, Sajjad Jalab, Hamid Abdullah Mazzola, Giuseppe Uliyan, Diaa Mohammed QA75 Electronic computers. Computer science Authenticating digital images is increasingly becoming important because digital images carry important information and due to their use in different areas such as courts of law as essential pieces of evidence. Nowadays, authenticating digital images is difficult because manipulating them has become easy as a result of powerful image processing software and human knowledge. The importance and relevance of digital image forensics has attracted various researchers to establish different techniques for detection in image forensics. The core category of image forensics is passive image forgery detection. One of the most important passive forgeries that affect the originality of the image is copy-move digital image forgery, which involves copying one part of the image onto another area of the same image. Various methods have been proposed to detect copy-move forgery that uses different types of transformations. The goal of this paper is to determine which copy-move forgery detection methods are best for different image attributes such as JPEG compression, scaling, rotation. The advantages and drawbacks of each method are also highlighted. Thus, the current state-of-the-art image forgery detection techniques are discussed along with their advantages and drawbacks. Springer Verlag 2018 Article PeerReviewed Sadeghi, Somayeh and Dadkhah, Sajjad and Jalab, Hamid Abdullah and Mazzola, Giuseppe and Uliyan, Diaa Mohammed (2018) State of the art in passive digital image forgery detection: copy-move image forgery. Pattern Analysis and Applications, 21 (2). pp. 291-306. ISSN 1433-7541, DOI https://doi.org/10.1007/s10044-017-0678-8 <https://doi.org/10.1007/s10044-017-0678-8>. https://doi.org/10.1007/s10044-017-0678-8 doi:10.1007/s10044-017-0678-8 |
| spellingShingle | QA75 Electronic computers. Computer science Sadeghi, Somayeh Dadkhah, Sajjad Jalab, Hamid Abdullah Mazzola, Giuseppe Uliyan, Diaa Mohammed State of the art in passive digital image forgery detection: copy-move image forgery |
| title | State of the art in passive digital image forgery detection: copy-move image forgery |
| title_full | State of the art in passive digital image forgery detection: copy-move image forgery |
| title_fullStr | State of the art in passive digital image forgery detection: copy-move image forgery |
| title_full_unstemmed | State of the art in passive digital image forgery detection: copy-move image forgery |
| title_short | State of the art in passive digital image forgery detection: copy-move image forgery |
| title_sort | state of the art in passive digital image forgery detection copy move image forgery |
| topic | QA75 Electronic computers. Computer science |
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