DCT-PCA Based Method for Copy-Move Forgery Detection

Copy move forgery detection is emerging as one of the hot research topic among researchers in the area of image forensics. There are many techniques suggested to detect such type of tampering with the original image but, many issues still remained either unsolved or there is a lot of scope for performance improvement. The most commonly used algorithm to detect such type of tampering is block matching algorithm. Robustness against post processing operations and the time taken by the detection techniques are few of the major challenges. Change of intensity of the copy moved part is one of the post processing operations that may be employed by the attacker to evade the image forgery detection methods. This is successfully addressed in the proposed algorithm. Discrete cosine transform and principal component analysis have been used to represent and compress the feature vector of overlapping blocks respectively. Features , invariant to local change of intensity are created using down sampling of low frequency DCT coefficients.