0393155 20240103202640.220130625235959.9 000318997700008 10.1016/j.diin.2013.02.007 11 s. P cav_un_epca*03115481742-2876101 (2013)73-84Elsevier Image forensic Copy–paste forgery Local block matching cav_un_auth*0291942 Sekeh M. A. MY cav_un_auth*0291943 Maarof M. A. MY cav_un_auth*0291944 Rohani M. F. MY cav_un_auth*0206076 Mahdian Babak Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2013/ZOI/mahdian-efficient image duplicated region detection model using sequential block clustering.pdf 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. 2014 IN 4 RVO:67985556 http://hdl.handle.net/11104/0221986 COMPUTERSCIENCEINFORMATIONSYSTEMS|COMPUTERSCIENCEINTERDISCIPLINARYAPPLICATIONS 1.171 0.205 4.III 0.00059 0.218 300 39 0.536 ScienceCitationIndexExpanded Q1 16.01 37.489 Q4 Q3 2013 000318997700008 WOS cav_un_epca*0311548 Digital Investigation 1742-2876 1873-202X Roč. 10 č. 1 2013 73 84 Elsevier