Copy move image forgery detection method using steerable pyramid transform and texture descriptor

In this paper, we propose a passive copy move image forgery detection method using a steerable pyramid transform (SPT) and Local Binary Pattern (LBP). SPT is applied on a grayscale version or one of the YCbCr channels of an image. LBP is applied to describe the texture in each SPT subband. Then the support vector machine (SVM) uses the LBP feature extracted from SPT sub-bands in classifying images into tampered or authentic images. Experimental results show an excellent effectiveness for the proposed method in some combinations of SPT sub-band.