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, Ce1,2 ; Ma, Qiang2 ; Xiao, Limei2 ; Li, Ming 2; Zhang, Aihua2
	2017-03-08
发表期刊	Neurocomputing
ISSN	09252312
卷号	228 页码:29-36
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.
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
DOI	10.1016/j.neucom.2016.04.068
收录类别	EI ; SCIE
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000393017900005
出版者	Elsevier B.V., Netherlands
EI入藏号	20165103149454
EI主题词	Color image processing
EI分类号	723 Computer Software, Data Handling and Applications ; 741.1 Light/Optics ; 903.1 Information Sources and Analysis ; 903.3 Information Retrieval and Use ; 921.3 Mathematical Transformations ; 922.1 Probability Theory
引用统计	被引频次：53[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/150593
专题	电气工程与信息工程学院机电工程学院
通讯作者	Li, Ce
作者单位	1.Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian 710049, Peoples R China; 2.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Peoples R China
第一作者单位	电气工程与信息工程学院
通讯作者单位	电气工程与信息工程学院
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.