With the advancement of high resolution digital cameras and photo editing software featuring new and advanced features the chances of image forgery has increased. The images can now be altered and manipulated easily. Image trustworthiness is now more in demand. Images in courtrooms for evidence, images in newspapers and magazines, and digital images used by doctors are few cases that demands for images with no manipulation. Some forgery images that result from portions copied and moved within the same image to “cover-up” something are called as copy-move forgeries. In previous year author use different-different methods such as Principle Component Analysis (PCA), Discrete Wavelet Transform (DWT) & Singular Value Decomposition (SVD) are time consuming. In past many of the algorithm were failed many times in the detection of forged image. Because single feature extraction algorithm is not capable to contain the specific feature of the images. So to overcome the limitation of existing algorithm we will use meta-fusion technique of HOG and Sasi features classifier also to overcome the limitation of SVM classifier. Logistic regression would be able to classify the forged image more precisely.