Revealing Image Splicing Forgery Using Local Binary Patterns of DCT Coefficients
The wide use of powerful image processing software has made it easy to tamper images for malicious purposes. Image splicing, which has constituted a menace to integrity and authenticity of images, is a very common and simple trick in image tampering. Ther
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Revealing Image Splicing Forgery Using Local Binary Patterns of DCT Coefficients Yujin Zhang, Chenglin Zhao, Yiming Pi, and Shenghong Li
Abstract The wide use of powerful image processing software has made it easy to tamper images for malicious purposes. Image splicing, which has constituted a menace to integrity and authenticity of images, is a very common and simple trick in image tampering. Therefore, image splicing detection is of great importance in digital forensics. In this chapter, an effective framework for revealing image splicing forgery is proposed. The local binary pattern (LBP) operator is used to model magnitude components of 2-D arrays obtained by applying multi-size block discrete cosine transform (MBDCT) to the test images, all of bins of histograms computed from LBP codes are served as discriminative features for image splicing detection. To avoid the high computational complexity and possible overfitting for support vector machine (SVM) classifier, principal component analysis (PCA) is utilized to reduce the dimensionality of the proposed features. Our experiment results demonstrate the efficiency of the proposed method over the Columbia image splicing detection evaluation dataset. Keywords Image splicing detection • Local binary pattern • DCT • PCA
Y. Zhang (*) • S. Li Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China e-mail: [email protected]; [email protected] C. Zhao School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China e-mail: [email protected] Y. Pi School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China e-mail: [email protected] Q. Liang et al. (eds.), Communications, Signal Processing, and Systems, Lecture Notes in Electrical Engineering 202, DOI 10.1007/978-1-4614-5803-6_19, # Springer Science+Business Media New York 2012
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Introduction
Image splicing is a very common and simple tampering manner which creates a composite image by cropping and pasting regions from the same or different images without postprocessing. Spliced images could be so eye-deceiving that they are scarcely distinguished from authentic ones even without any postprocessing. In addition, malicious image splicing manipulation may mislead the public and persuade them to believe something that never exists. Recently, many techniques have been developed to reveal image splicing tampering. Ng et al. in [1] proposed to use third order moment spectra (i.e. bicoherence) based features for splicing detection. It is claimed that bicoherence is sensitive to quadratic phase coupling (QPC) caused by splicing discontinuity. The detection accuracy as high as 72% over the image dataset [2] was achieved. Johnson and Farid in [3] developed a method to determine whether an image has been tampered with the assumption that both the original part and tampered part were taken under the same or approximately similar lighting conditi
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