In recent years, due to the increment in the image editing software applications and the easiness of using these, the probability of malicious changes on the images has also increased. Copy-move forgery is one of the most widely applied modification types on the images. In case of that the copied region is rotated before being pasted, forgery detection becomes difficult. Many researchers try on proposing new rotation-invariant techniques for detecting forgeries. For this purpose, various techniques such as Zernikeinvariants and log-polar transform have been utilized. In this study, Circular Projection technique is used for generating feature vectors from the image blocks. When compared with the results of the studies in the same field, it is observed that the proposed method gives better results even on the rotation operations with greater angles. Experimental results show that the proposed technique is robust against scaling and mirroring operations.