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Efficient Markov feature extraction method for image splicing detection using maximization and threshold expansion

[+] Author Affiliations
Jong Goo Han, Il Kyu Eom

Pusan National University, Department of Electronics Engineering, 2, Busandaehak-Ro 63 Beon-Gil, Geumjeong-Gu, Busan 46241, Republic of Korea

Tae Hee Park

TongMyong University, Department of Mechatronics Engineering, 428, Sinseon-Ro, Nam-Gu, Busan 48520, Republic of Korea

Yong Ho Moon

Gyeongsang National University, Department of Aerospace and Software Engineering, 501 Jinjudaro, Jinju 52828, Republic of Korea

J. Electron. Imaging. 25(2), 023031 (Apr 29, 2016). doi:10.1117/1.JEI.25.2.023031
History: Received December 15, 2015; Accepted April 11, 2016
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Abstract.  We propose an efficient Markov feature extraction method for color image splicing detection. The maximum value among the various directional difference values in the discrete cosine transform domain of three color channels is used to choose the Markov features. We show that the discriminability for slicing detection is increased through the maximization process from the point of view of the Kullback–Leibler divergence. In addition, we present a threshold expansion and Markov state decomposition algorithm. Threshold expansion reduces the information loss caused by the coefficient thresholding that is used to restrict the number of Markov features. To compensate the increased number of features due to the threshold expansion, we propose an even–odd Markov state decomposition algorithm. A fixed number of features, regardless of the difference directions, color channels and test datasets, are used in the proposed algorithm. We introduce three kinds of Markov feature vectors. The number of Markov features for splicing detection used in this paper is relatively small compared to the conventional methods, and our method does not require additional feature reduction algorithms. Through experimental simulations, we demonstrate that the proposed method achieves high performance in splicing detection.

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Citation

Jong Goo Han ; Tae Hee Park ; Yong Ho Moon and Il Kyu Eom
"Efficient Markov feature extraction method for image splicing detection using maximization and threshold expansion", J. Electron. Imaging. 25(2), 023031 (Apr 29, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.2.023031


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