Blur Invariant Image Forgery Detection Method Using Local Phase Quantization

With the rapid development of powerful image, editing software makes the forgery of the digital image easy. Researchers proposed methods to cope with image authentication in recent years. We proposed a passive image authentication technique to determine the copy move forgery that copied a part of an image and pasted it on the other region in the same image. First, the method divides the image into overlapping blocks. It uses LPQ (local phase quantization) to label each block. The column average value of labeled blocks constitutes the feature vector for the block. Similarity among the feature vectors gives a clue about the forgery. Local phase quantization has not been used to detect copy move forgery in the literature before. Experimental results show that, the method has higher accuracy ratios and lower false negative values under blurring operation at high levels compared to other methods. Our method can also detect multiple copy move forgery.