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Open Access Image Manipulation Detection Using Sensor Linear Pattern

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In this work, we introduce a new method for localizing image manipulations in a single digital image, such as identifying added, removed (spliced or in-painted), or deformed objects. The method utilizes the so-called Linear Pattern (LP) of digital images as a global template whose integrity can be assessed in a localized manner. The consistency of the linear pattern estimated from the image noise residual is evaluated in overlapping blocks of pixels. The manipulated region is identified by the lack of similarity in terms of the correlation coefficient computed between the power spectral density (PSD) of the LP in that region and the PSD averaged over the entire image. The method is potentially applicable to all images of sufficient resolution as long as the LP in the unmodified parts of the image has different spectral properties from that in the tampered area. No side information, such as the EXIF header or the camera model, is needed to make the method work. Experiments show the capability and limitations of the proposed method, which is robust to mild JPEG compression.
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Keywords: Image forensics; camera fingerprint; camera sensor pattern; forgery detection; image manipulation

Document Type: Research Article

Publication date: 28 January 2018

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