Copy-move forgery detection using improved SIFT

Yigang Zhou; Yunfang Xie

doi:10.1117/12.2244287

29 August 2016 Copy-move forgery detection using improved SIFT

Yigang Zhou, Yunfang Xie

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100334S (2016) https://doi.org/10.1117/12.2244287
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

Abstract

There are various forgeries in digital images without leaving any obvious traces of tampering due to powerful image processing and editing software. Copy-move forgery is a common type of image forgery in which a part of digital image is copied and pasted to another part in the same image with the intent of disguising some details. Based on scale invariant feature transform, a new blind detection method using Haar wavelet and ring descriptor is proposed in this paper. The method proposed not only makes the feature more stable and distinctive but also reduces the detection time dramatically. Results of experiment show that the method proposed is not only effective on different forgeries but also robust to post image processing, such as noise, blur, JPEG compression, scaling, rotation, or even compound image processing.

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Yigang Zhou and Yunfang Xie "Copy-move forgery detection using improved SIFT ", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100334S (29 August 2016); https://doi.org/10.1117/12.2244287

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KEYWORDS

Image processing

Wavelets

Image compression

Digital watermarking

Detection and tracking algorithms

Convolution

Databases

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