Efficient image duplicated region detection model using sequential block clustering
Apart from robustness and accuracy of copy–paste image forgery detection, time complexity also plays an important role to evaluate the performance of the system. In this paper, the focus point is to improve time complexity of the block-matching algorithm. Hence, a coarse-to-fine approach is applied...
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| Published in | Digital investigation Vol. 10; no. 1; pp. 73 - 84 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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Elsevier Ltd
01.06.2013
Elsevier Science Ltd |
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| Online Access | Get full text |
| ISSN | 1742-2876 1873-202X |
| DOI | 10.1016/j.diin.2013.02.007 |
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| Abstract | Apart from robustness and accuracy of copy–paste image forgery detection, time complexity also plays an important role to evaluate the performance of the system. In this paper, the focus point is to improve time complexity of the block-matching algorithm. Hence, a coarse-to-fine approach is applied to propose an enhanced duplicated region detection model by using sequential block clustering. Clustering minimizes the search space in block matching. This significantly improves time complexity as it eliminates several extra block-comparing operations. We determine time complexity function of the proposed algorithm to measure the performance. The experimental results and mathematical analysis demonstrate that our proposed algorithm has more improvement in time complexity when the block size is small. |
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| AbstractList | Apart from robustness and accuracy of copy-paste image forgery detection, time complexity also plays an important role to evaluate the performance of the system. In this paper, the focus point is to improve time complexity of the block-matching algorithm. Hence, a coarse-to-fine approach is applied to propose an enhanced duplicated region detection model by using sequential block clustering. Clustering minimizes the search space in block matching. This significantly improves time complexity as it eliminates several extra block-comparing operations. We determine time complexity function of the proposed algorithm to measure the performance. The experimental results and mathematical analysis demonstrate that our proposed algorithm has more improvement in time complexity when the block size is small. [PUBLICATION ABSTRACT] Apart from robustness and accuracy of copy–paste image forgery detection, time complexity also plays an important role to evaluate the performance of the system. In this paper, the focus point is to improve time complexity of the block-matching algorithm. Hence, a coarse-to-fine approach is applied to propose an enhanced duplicated region detection model by using sequential block clustering. Clustering minimizes the search space in block matching. This significantly improves time complexity as it eliminates several extra block-comparing operations. We determine time complexity function of the proposed algorithm to measure the performance. The experimental results and mathematical analysis demonstrate that our proposed algorithm has more improvement in time complexity when the block size is small. |
| Author | Rohani, Mohd. Foad Maarof, Mohd. Aizaini Mahdian, Babak Akbarpour Sekeh, Mohammad |
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| Cites_doi | 10.1016/j.forsciint.2006.11.002 10.1016/j.image.2010.05.003 10.1016/j.sigpro.2011.01.022 10.4156/jdcta.vol5.issue1.27 10.1109/TIFS.2010.2078506 10.4304/jmm.7.1.90-97 10.1109/TIFS.2012.2218597 10.1007/11427445_121 10.1016/j.forsciint.2010.08.001 10.21136/AM.1981.103933 |
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| Keywords | Duplicated region detection Block clustering Image forensic Time complexity Local block matching Copy–paste forgery |
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| SubjectTerms | Algorithms Block clustering Copy–paste forgery Duplicated region detection Forgery Image forensic Local block matching Mathematical analysis Performance evaluation Time complexity |
| Title | Efficient image duplicated region detection model using sequential block clustering |
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