Huang et al., 2008 - Google Patents
Detection of copy-move forgery in digital images using SIFT algorithmHuang et al., 2008
View PDF- Document ID
- 4115799731958329019
- Author
- Huang H
- Guo W
- Zhang Y
- Publication year
- Publication venue
- 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application
External Links
Snippet
As result of powerful image processing tools, digital image forgeries have already become a serious social problem. In this paper we describe an effective method to detect Copy-Move forgery in digital images. This method works by first extracting SIFT descriptors of an image …
- 238000001514 detection method 0 title description 26
Classifications
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- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/52—Extraction of features or characteristics of the image by deriving mathematical or geometrical properties from the whole image
- G06K9/527—Scale-space domain transformation, e.g. with wavelet analysis
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
- G06K9/6203—Shifting or otherwise transforming the patterns to accommodate for positional errors
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- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
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- G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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- G—PHYSICS
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