Digital Image Splicing Detection Based on Local Complexity of Local Maximum Partial Gradient of DWT Coefficients

Zimba, Michael; Sun Xingming
March 2012
International Journal of Digital Content Technology & its Applic;Mar2012, Vol. 6 Issue 5, p1
Academic Journal
In this paper, we propose a novel method for detecting image splicing forgery by thresholding transition region measures of discrete wavelet transform (DWT) coefficients of a suspicious image in chroma spaces. DWT of a suspicious image is performed and only its low frequency subband is extracted to reduce the size of the image. Since image splicing is usually disguised in RGB and luminance spaces, chroma spaces of the subband are preferably extracted as they reveal discontinuities introduced by splicing. A fixed square lattice is run pixel by pixel from top-left corner to the bottom-right corner of each chroma channel of the subband in a raster-scan order, computing a local maximum partial gradient (LMPG) at each pixel location. Consequently, an LMPG image is formed. Local complexity of the LMPG image is subsequently computed at each pixel location. LMPG not only reflects the degree of the DWT coefficient changes, but also de-correlates the image by removing most of the image information except abrupt changes in the pixel values. At the same time, local complexity determines the frequency of the coefficient changes. Appropriate thresholds of the two transition region measures isolate traces of image splicing. The proposed method is faster than the existing methods because the dimensions of the suspicious image are reduced and both LMPG and local complexity are time-efficient measures of pixel changes. With an overall accuracy of 82%, the results from experiments conducted on several spliced and authentic images demonstrate the viability of the proposed algorithm.


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