收稿日期: 2017-02-13
修回日期: 2017-03-15
网络出版日期: 2017-11-30
基金资助
国家自然科学基金（No.61772281，No.61272421，No.61232016，No.61402235，No.61502241）；江苏省自然科学基金（No.BK20141006）；江苏高校优势学科建设工程项目和大气环境与装备技术协同创新中心基金资助
Splicing Detection for Color Images Based on QDCT Markov method
Received date: 2017-02-13
Revised date: 2017-03-15
Online published: 2017-11-30
王金伟, 刘仁峰 . 基于QDCT马尔科夫方法的彩色图像拼接检测[J]. 应用科学学报, 2017 , 35(6) : 754 -762 . DOI: 10.3969/j.issn.0255-8297.2017.06.009
We propose a splicing detection scheme based on quaternion discrete cosine transform (QDCT). The scheme uses correlation among three channels of a color image to reduce loss of the image's inherent color information. QDCT is first applied to the images, and features are extracted with the proposed scheme in the QDCT domain. SVM is used to detect image splicing. Using the image bases CASIA1 and CASIA2, accuracy of the proposed scheme reaches 98.75% and 96.78% respectively, which is better than most of existing methods.
[1] Hsiao D Y, Pei S C. Detecting digital tampering by blur estimation[C]//First International Workshop on Systematic Approaches to Digital Forensic Engineering, IEEE, 2005:264-278.
[2] Kakar P, Sudha N, Ser W. Exposing digital image forgeries by detecting discrepancies in motion blur[J]. IEEE Transactions on Multimedia, 2011, 13(3):443-452.
[3] Bahrami K, Kot A C, Li L. Blurred image splicing localization by exposing blur type inconsistency[J]. IEEE Transactions on Information Forensics and Security, 2015, 10(5):999-1009.
[4] Rao M P, Rajagopalan A N, Seetharaman G. Harnessing motion blur to unveil splicing[J]. IEEE Transactions on Information Forensics and Security, 2014, 9(4):583-595.
[5] Hsu Y F, Chang S F. Camera response functions for image forensics:an automatic algorithm for splicing detection[J]. IEEE Transactions on Information Forensics & Security, 2010, 5(4):816-825.
[6] Yao H, Wang S, Zhang X. Detecting image splicing based on noise level inconsistency[J]. Multimedia Tools & Applications, 2016:1-23.
[7] Farid H, Lü S. Higher-order wavelet statistics and their application to digital forensics[C]//Conference on Computer Vision and Pattern Recognition Workshop, CVPRW'03, 2003, 8:94-94.
[8] Fu D, Shi Y Q, Su W. Detection of image splicing based on Hilbert-Huang transform and moments of characteristic functions with wavelet decomposition[C]//International Workshop on Digital Watermarking. Berlin Heidelberg:Springer, 2006:177-187.
[9] 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, 2007:51-62.
[10] Wang W, Dong J, Tan T. Effective image splicing detection based on image chroma[C]//200916th IEEE International Conference on Image Processing (ICIP), 2009:1257-1260.
[11] Sutthiwan P, Shi Y Q, Zhao H. Markovian rake transform for digital image tampering detection[M]//Transactions on Data Hiding and Multimedia Security VI. Berlin Heidelberg:Springer, 2011:1-17.
[12] He Z, Lu W, Sun W. Digital image splicing detection based on Markov features in DCT and DWT domain[J]. Pattern Recognition, 2012, 45(12):4292-4299.
[13] 袁全桥,苏波,赵旭东. 基于高频小波子带马尔科夫特征的图像拼接检测[J]. 计算机应用,2014, 34(5):1477-1481. Yuan Q Q, Su B, Zhao X D. A new adaptive bilateral filtering[J]. Journal of Computer Applications, 2014, 34(5):1477-1481. (in Chinese)
[14] El-Alfy E S M, Qureshi MA. Combining spatial and DCT based Markov features for enhanced blind detection of image splicing[J]. Pattern Analysis and Applications, 2015, 18(3):713-723.
[15] Ng T T, Chang S F, Sun Q. A data set of authentic and spliced image blocks[R]. Advent Technical Report, Columbia University, 2004.
[16] Li C, Ma Q, Xiao L. Image splicing detection based on Markov features in QDCT domain[M]//Advanced Intelligent Computing Theories and Applications.[S.l.]:Springer International Publishing, 2015:297-303.
[17] Dong J, Wang W. CASIA tampered image detection evaluation database[DB]. http://forensics. idealtest.org/.
[18] Muhammad G, Al-Hammadi M H, Hussain M, Bebis G. Image forgery detection using steerable pyramid transform and local binary pattern[J]. Machine Vision and Applications, 2014, 25(4):985-995.
[19] Hamilton W R. Elements of quaternions[M]. London:Longmans, Green and Company, 1866.
[20] Feng W, Hu B. Quaternion discrete cosine transform and its application in color template matching[C]//Congress on Image and Signal Processing, CISP'08, 2008, 2:252-256.
[21] 熊邦书,刘雨,莫燕. 基于SVM的直升机飞行状态识别[J]. 应用科学学报,2016, 34(4):469-474. Xiong B S, Liu Y, Mo Y. Recognition of helicopter flight condition based on support vector machine[J]. Journal of Applied Sciences, 2016, 34(4):469-474. (in Chinese)
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