Image splicing detection based on markov features in QDCT domain

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 9227, Issue , 2015, Pages 297-303

  Li, Ce ^a,b   Ma, Qiang ^a   Xiao, Limei ^a   Li, Ming ^a   Zhang, Aihua ^a  

^a LANZHOU UNIVERSITY OF TECHNOLOGY   (China)

^b XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

Color image forgery detection; Image splicing detection; Markov model; QDCT

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); COLOR IMAGE PROCESSING; DISCRETE COSINE TRANSFORMS; INFORMATION USE; INTELLIGENT COMPUTING; MARKOV PROCESSES; SUPPORT VECTOR MACHINES;

CLASSIFICATION ACCURACY; CLASSIFICATION ALGORITHM; COLOR IMAGES; COLOR INFORMATION; DIGITAL FORENSIC; IMAGE SPLICING DETECTION; MARKOV MODEL; QDCT;

COLOR;

EID: 84983593589     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-22053-6_32     Document Type: Conference Paper

References (12)

1. Shi, Y.Q., Chen, C., Chen, W.: A natural image model approach to splicing detection. In: ACM Proceedings of the 9th Workshop on Multimedia and Security, pp. 51-62 (2007)
2. Ng, T.T., Chang, S.F., Sun, Q.: A Data Set of Authentic and Spliced Image Blocks. Columbia University, New York (2004)
3. Wang, W., Dong, J., Tan, T.: Effective image splicing detection based on image chroma. In: IEEE International Conference on Image Processing, pp. 1257-1260 (2009)
4. Wang, W., Dong, J., Tan, T.: Image tampering detection based on stationary distribution of Markov chain. In: IEEE international Conference on Image Processing, pp. 2101-2104 (2010)
5. http://forensics.idealtest.org/
6. Sutthiwan, P., Shi, Y.Q., Zhao, H., Ng, T.-T., Su, W.: Markovian rake transform for digital image tampering detection. In: Shi, Y.Q., Emmanuel, S., Kankanhalli, M.S., Chang, S.-F., Radhakrishnan, R., Ma, F., Zhao, L. (eds.) Transactions on Data Hiding and Multimedia Security VI. LNCS, vol. 6730, pp. 1-17. Springer, Heidelberg (2011)
7. Zhao, X., et al.: Passive image-splicing detection by a 2-D noncausal Markov model. IEEE Trans. Circ. Syst. Video Technol. 2(25), 185-199 (2014)
8. He, Z., Wei, L., Sun, W., et al.: Digital image splicing detection based on Markov features in DCT and DWT domain. Pattern Recogn. 45(12), 4292-4299 (2012)
9. Amerini, I., Becarelli, R., et al.: Splicing forgeries localization through the use of first digit features. In: IEEE Conference on Parallel Computing Technologies, pp. 143-148 (2015)
10. Feng, W., Hu, B.: Quaternion discrete cosine transform and its application in color template matching. IEEE Congr. Image Sig. Process. 5(2), 252-256 (2008)
11. Schauerte, B., Stiefelhagen, R.: Quaternion-based spectral saliency detection for eye fixation prediction. In: European Conference on Computer Vision, pp. 116-129 (2012)
12. Chapelle, O.: Training a support vetor machine in the primal. Neural Comput. 19(5), 1155-1178 (2007)