Digital images can be forged easily with today’s widely available ima ge processing software. One of the most common practices in image tampering involves cropping a patch fr om a source and pasting it onto a target.This task,when images are used as evidence to influen ce or decide judgment such as in a court of law,can be crucial.A novel image forensic method based o n coefficient-pair histogram in discrete cosine transform (DCT) domain is proposed.In the method, firstly,the image is transformed by DCT,then with the given threshold,coefficient-pa ir histogram is computed for the DCT coefficients,and normalization processing is excuted on the coefficient-pa ir histogram.After that, principal component analysis (PCA) is used to reduce the dimension of the above data to get the final image features.Lastly,support vector machine (SVM) is exploited to classify th e authentic and spliced images through training the feature vectors of them. In CASIA v1.0,the recognition rate reach 97.92%,and it is 91.20% in CASIA v2.0.The experim ental results show that compared with some existing methods, the proposed approach has low com puting complexity and good recognition performance in both uncompressed and comp ressed images.