Information Hiding Techniques for Steganography and Digital Watermarking
Information Hiding Techniques for Steganography and Digital Watermarking
Shape Indexing Using Approximate Nearest-Neighbour Search in High-Dimensional Spaces
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Robust Detection of Region-Duplication Forgery in Digital Image
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Detection of Region Duplication Forgery in Digital Images Using Wavelets and Log-Polar Mapping
ICCIMA '07 Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007) - Volume 03
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Detection of Copy-Move Forgery in Digital Images Using SIFT Algorithm
PACIIA '08 Proceedings of the 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application - Volume 02
An efficient and robust method for detecting copy-move forgery
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Image Copy-Move Forgery Detection Based on SURF
MINES '10 Proceedings of the 2010 International Conference on Multimedia Information Networking and Security
Region duplication detection using image feature matching
IEEE Transactions on Information Forensics and Security
Structural digital signature for image authentication: an incidental distortion resistant scheme
IEEE Transactions on Multimedia
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Region duplication is a simple and effective operation for digital image forgeries. The detection of region duplication is very important in digital image forensics. Most existing detection methods for region duplication are based on exhaustive block-matching of image pixels or transform coefficients. They may not be effective when the duplicate regions have gone through some geometrical transformations. In this paper, a novel region duplication detection method that is robust to general geometrical transformations is proposed. Firstly, the Harris corner interest points in an image are detected. Then, an image region description method based on step sector statistics is developed to represent the small circle image region around each Harris point with a feature vector. Finally, the small circle image regions are matched using the best-bin-first algorithm to reveal duplicate regions. Experimental results show that the proposed method can work effectively on the forged images from two image databases, and it is also robust to several geometrical transformations and image degradations.