Passive detection of image forgery using DCT and local binary pattern. Issue 1 (January 2017)

• Record Type: Journal Article
• Authors: Alahmadi, Amani; Hussain, Muhammad; Aboalsamh, Hatim; Muhammad, Ghulam; Bebis, George; Mathkour, Hassan
• Is Part Of: Signal, image and video processing. Volume 11:Issue 1(2017)
• Page Start: 81
• Page End: 88
• Publication Date: 2017-01
• Subjects: Copy–move forgery -- Image splicing -- Forgery detection -- Image forensics -- LBP -- DCT -- SVM; Signal processing -- Digital techniques -- Periodicals; Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; 621.3822
• DOI: 10.1007/s11760-016-0899-0
• Languages: English
• ISSNs: 1863-1703

Abstract

Abstract With the development of easy-to-use and sophisticated image editing software, the alteration of the contents of digital images has become very easy to do and hard to detect. A digital image is a very rich source of information and can capture any event perfectly, but because of this reason, its authenticity is questionable. In this paper, a novel passive image forgery detection method is proposed based on local binary pattern (LBP) and discrete cosine transform (DCT) to detect copy–move and splicing forgeries. First, from the chrominance component of the input image, discriminative localized features are extracted by applying 2D DCT in LBP space. Then, support vector machine is used for detection. Experiments carried out on three image forgery benchmark datasets demonstrate the superiority of the method over recent methods in terms of detection accuracy.