ISSN: 2277 – 9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 5, July 2012 56 All Rights Reserved © 2012 IJARCSEE Abstract— In an age with digital media, it is no longer true that seeing is believing.In addition, digital forgeries, can be indistinguishable from authentic photographs. In a copy-move image forgery, a part of an image is copied and then pasted on a different location within the same image .In this paper an improved algorithm based on Discrete Wavelet Transform (DWT)is used to detect such cloning forgery. In this technique DWT (Discrete Wavelet Transform) is applied to the input image to yield a reduced dimensional representation.After that compressed image is divided into overlapping blocks. These blocks are then sorted and duplicated blocks are identified. Due to DWT usage, detection is first carried out on lowest level image representation so this Copy-Move detection process increases accuracy of detection process. Keywords- Digital Tempering,DWT Copy-Move forgery. I INTRODUCTION Copy-Move forgery is performed with the intention to make an object ―disappear‖ from the image by covering it with a small block copied from another part of the same image[1]. Usually, such an image tampering is done with the aim of either hiding some image details, in which case a background is duplicated, or adding more details. Whichever the case, image integrity is lost.Because the copied segments come from the same image, the color palette, noise components, dynamic range and the other properties will be compatible with the rest of the image, thus it is very difficult for a human eye to detect. Sometimes, even it makes harder for technology to detect the forgery, if the image is retouched with the tools that are available. Figure 1. Example of Copy-Move forgery (a) original image (b) tampered image Manuscript received July, 2012 Preeti Yadav:, Final year M-Tech CSE, CSVTU Bhilai,RITEE Raipur, (e-mail:preetiyadu@yahoo.co.in).Raipur, India,Mobile-9827974272 Yogesh Rathore:, :, Department of CSE, CSVTU Bhilai,RITEE Raipur, (e-mail:yogeshrathore23@gmail.com).Raipur, India,le-Mobi9301058533. Aarti Yadu, Department of IT, CSVTU Bhilai,RITEE Raipur, (e-mail:artiyadu@gmail.com).Raipur, India. II. LITERATURE REVIEW Since the key characteristics of Copy-Move forgery is that the copied part and the pasted part are in the same image, one method to detect this forgery is exhaustive search, but it is computationally complex and more time is needed for detection. A. C. Popescu and H. Farid proposed a similar detection method [2], in which the image blocks are reduced in dimension by using Principal Component Analysis (PCA). But the efficiency of detection algorithm was not good, because, blocks are directly extracted from the original image, resulting in a large number of blocks. D. Soukal, proposes DCT based copy-move forgery detection in a single image, In which The image blocks are represented by quantized DCT (Discrete Cosine Transform) coefficients, and a lexicographic sort is adopted to detect the duplicated image blocks [3]. B.L.Shivakumar and Dr. S.Santhosh Baboo have proposed copy-move forgery detection method based on SURF, which detects duplication region with different size. Experimental result shows that the proposed method can detect copy-move forgery with minimum false match for images with high resolution[4] . To increase the speed of operation process many researchers use blocking approaches [5]. G.Li, Q.Wu, D.Tu developed a sorted neighborhood method based on DWT (Discrete Wavelet Transform) and SVD (Singular Value Decomposition) [6].In this method the computation of SVD takes lot of time and it is computationally complex. III. PROPOSED METHOD In this proposed method an image is scanned from the upper left corner to the lower right corner while sliding a B×B block. The DWT transform is calculated For each block, the DWT coefficients are stored as one row in the matrix A. The matrix will have (M+B+1)(N–B+1) rows and B×B columns.The rows of A are lexicographically sorted . The DWT coefficients for each block are now being compared instead of the pixel representation, if two successive rows of the sorted matrix A are found, the algorithm stores the positions of the matching blocks in a separate list B,and increments a shift-vector counter C. For all normalized shift vectors, the matching blocks that contributed to that specific shift vector are colored with the same color and thus identified as segments that might have been copied and moved. The Proposed method of copy-move forgery detection has following main parts. 1. Discrete Wavelet Transform 2. Lexicographic Sorting 3. Shift Vector Calculation 4. Neighbor block matching 3.1 Discrete Wavelet Transform DWT Based Copy-Move Image Forgery Detection Preeti Yadav ,Yogesh Rathore ,Aarti Yadu