Image splicing detection based on Markov features in QDCT domain

doi:10.1016/j.neucom.2016.04.068

	Image splicing detection based on Markov features in QDCT domain
	Li, Ce 1,2; Ma, Qiang 1; Xiao, Limei 1; Li, Ming 1; Zhang, Aihua 1
刊名	Neurocomputing
	2017-03-08
卷号	228 页码:29-36
关键词	Classification (of information) Color Digital forensics Discrete cosine transforms Information use Markov processes Support vector machines Classification algorithm Color images Detection performance Image splicing Image splicing detection Inter-block correlations Markov model Transition probability matrix
ISSN号	09252312
DOI	10.1016/j.neucom.2016.04.068
英文摘要	Image splicing is very common and fundamental in image tampering. Therefore, image splicing detection has attracted more and more attention recently in digital forensics. Gray images are used directly, or color images are converted to gray images before be processed in previous image splicing detection algorithms. However, most forgery images are color images. In order to make use of the color information in images, a classification algorithm is put forward which can use color images directly. In this paper, an algorithm based on Markov in quaternion discrete cosine transform (QDCT) domain is proposed for image splicing detection. First of all, color information is extracted from blocked images to construct quaternion in a whole manner, and the QDCT coefficients of quaternion blocked images can be obtained. Secondly, the expanded Markov features generated from the transition probability matrices in QDCT domain can not only capture the intra-block, but also the inter-block correlation between block QDCT coefficients. Finally, support vector machine (SVM) is exploited to classify the Markov feature vector. The experiment results demonstrate that the proposed algorithm not only make use of color information of images, but also can yield considerably better detection performance compared with the state-of-the-art splicing detection methods tested on the same dataset. © 2016 Elsevier B.V.
WOS研究方向	Computer Science
语种	英语
出版者	Elsevier B.V., Netherlands
WOS记录号	WOS:000393017900005
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/150593]
专题	电气工程与信息工程学院
作者单位	1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou; 730050, China 2.School of Electronic and Information Engineering, Xian Jiaotong University, Xian; 710049, China;
推荐引用方式 GB/T 7714	Li, Ce,Ma, Qiang,Xiao, Limei,et al. Image splicing detection based on Markov features in QDCT domain[J]. Neurocomputing,2017,228:29-36.
APA	Li, Ce,Ma, Qiang,Xiao, Limei,Li, Ming,&Zhang, Aihua.(2017).Image splicing detection based on Markov features in QDCT domain.Neurocomputing,228,29-36.
MLA	Li, Ce,et al."Image splicing detection based on Markov features in QDCT domain".Neurocomputing 228(2017):29-36.