As the increased availability of sophisticated image processing software and the widespread use of Internet, digital images are easy to acquire and manipulate. The authenticity of the received images is becoming more and more important. Copy-move forgery is one of the most common forgery methods. When creating a Copy-move forgery, it is often necessary to add or remove important features from an image. To carry out such forensic analysis, various technological instruments have been developed in the literatures. However, most of them are time-consuming. In this paper, a more efficient method is proposed. First, the image size is reduced by Discrete Wavelet Transform (DWT). Second, the image is divided into overlapping blocks of equal size and, feature of each block is extracted by fast Walsh-Hadamard Transform (FWHT). Duplicated regions are then detected by lexicographically sorting all features of the image blocks. To make the range matching more efficient, multi-hop jump (MHJ) algorithm is using to jump over some the “unnecessary testing blocks” (UTB). Experimental results demonstrated that the proposed method not only is able to detect the copy-move forgery accurately but also can reduce the processing time greatly compared with other methods.