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http://dx.doi.org/10.7471/ikeee.2018.22.2.227

Fast Image Splicing Detection Algorithm Using Markov Features  

Kim, Soo-min (Dept. of Computer Education, Sungkyunkwan University)
Park, Chun-Su (Dept. of Computer Education, Sungkyunkwan University)
Publication Information
Journal of IKEEE / v.22, no.2, 2018 , pp. 227-232 More about this Journal
Abstract
Nowadays, image manipulation is enormously popular and easier than ever with tons of convenient images editing tools. After several simple operations, users can get visually attractive images which easily trick viewers. In this paper, we propose a fast algorithm which can detect the image splicing using the Markov features. The proposed algorithm reduces the computational complexity by removing unnecessary Markov features which are not used in the image splicing detection process. The performance of the proposed algorithm is evaluated using a famous image splicing dataset which is publicly available. The experimental results show that the proposed technique outperforms the state-of-the-art splicing detection methods.
Keywords
Image Splicing; Markov Features; Transition Probability Matrix; DCT Domain; SVM;
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Times Cited By KSCI : 1  (Citation Analysis)
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