数字图像复制粘贴篡改取证

Abstract

Abstract: When a digital image is tampered with copy and paste,the copied part might be zoomed,rotated and then pasted in different parts of the image.The sift key points are detected in the image by SIFT algorithm,and the matched key points are found out by matching vector of the key points.The matched key points are classified by the affine transformation matrix which is calculated byRANdom SAmple Consensus,namely randomly extracting three matched point pairs in matched point pairs.The affine transformation of the image and its inverse affine transformation are carried out.Then the local correlation map of the tampered image and its affine transformation image is obtained,and the local correlation map of the tampered image and its inverse affine transformation image too.Each class of matched key points is divided into two groups according to affine transformation relations.A binary image is set from the key point of each group and dilated with structural elements.The dilated position of the binary image is continued to have when its value in the local correlation map is greater than the threshold and is get rid of when its value in the local correlation map is less than the threshold.The binary image is dilated iteratively until it’s no longer expands and its boundary is marked on the original image.Experiments show that this method can effectively locate the copy paste tampering areas in digital images.

Key words: Copy-pasted forgery, Digital image forensics, Local correlation map, RANSAC algorithm, Sift key points

CLC Number:

TP391

XING Wen-bo, DU Zhi-chun. Digital Image Forensics for Copy and Paste Tampering[J].Computer Science, 2019, 46(6A): 380-384.

References

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