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Digital Image Forensics

Digital Image Forensics. CS 365 By:- - Abhijit Sarang - Pankaj Jindal. Which of them are digitally manipulated?. How can we know?.

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Digital Image Forensics

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  1. Digital Image Forensics CS 365 By:- • - Abhijit Sarang • - Pankaj Jindal

  2. Which of them are digitally manipulated?

  3. How can we know? • We call a digital image manipulated if either it has been retouched by a photo editing software or has been produced by the software itself. • To prevent the former, the owner of the original image may introduce a watermark or a digital signature. • But this process may not be feasible every time. • Most approaches for detecting digital image manipulation are blind approaches.

  4. Our Methodology • In [1], the authors argue that the statistical artifacts associated with images generated from cameras is inherently different form that associated with images manipulated by a software. • These properties can be captured by analyzing the noise present in the image. • Further, a discrete wavelet transform of the image can also be used to obtain some other statistical features .

  5. Building the feature vectors • Image De-noising • Image was filtered using a wiener adaptive filter and a median filter. • Neighborhood model of Wavelet sub bands • To capture the strong correlation that exists between the wavelet subband coefficient, we find the residual error by building a neighborhood prediction model. • Discrete wavelet transform • We find the distance of the sub-bands distribution from the corresponding Gaussian distribution.

  6. Results • Image denoising • True Positive = 37/47 • False Positive = 21/53 • Neighborhood model of Wavelet sub bands • True Positive = 32/47 • False Positive = 11/53 • Discrete wavelet transform • True Positive = 34/47 • False positive = 15/53

  7. Detecting Fake Regions • Detecting abnormal noise patterns in Image • Detecting Duplicated Image Regions

  8. References • Digital image Forensics For Identifying Computer Generated And Digital Camera Images • Sintayehu Dehnie, Taha Sencar and Nasir Memon • Exposing Digital Forgeries by Detecting Duplicated Image Regions • Alin C Popescu and Hany Farid • Noise Features for Image Tampering Detection and Steganalysis • Hongmei Gou, Swaminathan, A., Min Wu • How realistic is photorealistic? • Siwei Lyu and Hany Farid

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