吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (2): 446-453.doi: 10.13229/j.cnki.jdxbgxb201402027

• paper • Previous Articles     Next Articles

Blind detection of image splicing based on visual attention model and extended hidden Markov model

SHEN Xuan-jing1,2, LI Xiang1,2, LYU Ying-da1,2, CHEN Hai-peng1,2   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China;
    2. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
  • Received:2012-12-27 Online:2014-02-01 Published:2014-02-01

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Abstract:

In order to improve the detection accuracy of spliced images, a new blind detection based on the Visual Attention Model (VAM) was proposed in this study. First, the Edge Conspicuous Map (ECM) is created by an improved Order Statistics Filter (OSF) based nonlinear filtering approach; then, the ECM fixations are extracted by VAM, and the fixations on the boundaries are located by conspicuous edge positioning method, accordingly the key feature fragments are captured. Second, the Extended Hidden Markov Model (E-HMM) features are extracted from each wavelet reconstructed image of Cr channel of the fragments, and their dimensions are reduced by SVM-RFE. Finally, the above features are trained and classified using SVM, by which the spliced images can be identified from the natural ones. The experimental results show that, when testing on the Columbia image splicing detection dataset, the detection accuracy of the proposed method is 96.32%.

Key words: computer application, blind identification, image splicing, visual attention model, extended hidden Markov model

CLC Number: 

  • TP391

[1] 吕颖达, 申铉京, 苗健, 等.基于光源方向不一致性的局部光源图像盲鉴别方法[J].吉林大学学报:工学版, 2010, 40(6):1673-1677. LV Ying-da, Shen Xuan-jing, Miao Jian, et al.Blind identification for light source images based on inconsistency in light source direction[J].Journal of Jilin University(Engineering and Technology Edition), 2010, 40(6):1673-1677.

[2] 吴琼, 李国辉, 涂丹, 等. 面向真实性鉴别的数字图像盲取证技术综述[J].自动化学报, 2008, 34(12): 1458-1466. Wu Qiong, Li Guo-hui, Tu Dan, et al. A survey of blind digital image forensics technology for authenticity detection[J]. Acta Automatica Sinica, 2008, 34(12): 1458-1466.

[3] Qu Z, Qiu G, Huang J. Detect digital image splicing with visual cues[C]//Information Hiding.Berlin:Springer Berlin Heidelberg, 2009.

[4] Ng T T, Chang S F, Sun Q. A data set of authentic and spliced image blocks[R]. Columbia University, ADVENT Technical Report, 2004: 203-204.

[5] Lin Z, He J, Tang X, et al. Fast, automatic and fine-grained tampered JPEG image detection via DCT coefficient analysis[J]. Pattern Recognition, 2009, 42(11): 2492-2501.

[6] Zheng Q, Sun W, Lu W. Digital spliced image forensics based on edge blur measurement[C]// 2010 IEEE International Conference on Information Theory and Information Security, Beijing, China, 2010.

[7] Dong J, Wang W, Tan T, et al. Run-length and Edge Statistics Based Approach for Image Splicing detection[M]. Berlin:Springer Berlin Heidelberg, 2009.

[8] He Z, Sun W, Lu W, et al. Digital image splicing detection based on approximate run length[J]. Pattern Recognition Letters, 2011, 32(12): 1591-1597.

[9] Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1998, 20(11): 1254-1259.

[10] Shi Y Q, Chen C, Chen W. A natural image model approach to splicing detection[C]//Proceedings of the 9th Workshop on Multimedia & Security, ACM, 2007.

[11] Zhao X, Li J, Li S, et al. Detecting Digital Image Splicing in Chroma Spaces[M]. Berlin:Springer Berlin Heidelberg, 2011.

[12] Guyon I, Weston J, Barnhill S, et al. Gene selection for cancer classification using support vector machines[J]. Machine Learning, 2002, 46(1-3): 389-422.

[13] Chang C C, Lin C J. LIBSVM: a library for support vector machines[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2011, 2(3): 27.

[14] Hsu C W, Chang C C, Lin C J. A practical guide to support vector classification[R].Department of Computer Science and Information Engineering, National Taiwan University, Taipei, 2003.
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