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Presenting - Anat Kaspi

Exposing Digital Forgeries in Color Filter Array Interpolated Images By Alin C. Popescu and Hany Farid. Presenting - Anat Kaspi. The Goal. Low cost high resolution digital camera, sophisticated photo editing  Digital media can be manipulated very easily Fake images…

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Presenting - Anat Kaspi

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  1. Exposing Digital Forgeries in Color Filter Array Interpolated ImagesBy Alin C. Popescu and Hany Farid Presenting - Anat Kaspi

  2. TheGoal • Low cost high resolution digital camera, sophisticated photo editing  Digital media can be manipulated very easily • Fake images… • Photos no longer hold the unique stature as a definitive recording of events Automatically detecting digital forgeries in any portion of an image • In contrast to other approaches: watermark, signature Drawback: must be inserted at time of recording

  3. The Technique Digital forgeries may leave no visual clues but they may alter the underlying statistics of an image • Color image consists of three channels containing samples from different bands of the color spectrum • Most digital cameras are equipped with only a single color sensor and use Color Filter Array (CFA) • The other two missing colors must be estimated from the neighboring to obtain three channel color images – CFA Interpolation

  4. The Technique (Cont.) • A subset of samples, within a color channel, are correlated to neighboring samples • The correlations are periodic since the color filters arranged in a periodic pattern Presence or lack of correlation produced by CFA interpolation can be used to detect forgery • There are many CFA Interpolation algorithms • Bilinear and Bicubic, Median Filter, Gradient Based, Adaptive Color Plane and more…

  5. Example Bilinear interpolation TheEstimatedsamples are perfectly correlated to their neighbors

  6. The Method - EM Algorithm • Two step iterative algorithm • We have two models: M1, M2 • Outputs: • Probability Map – detect if a color image is a result of CFA interpolation • Linear coefficients – used to distinguish between different CFA interpolation

  7. Results • CFA interpolation of their creation • Each color channel was independently blurred with 3x3 binomial filter • Down sample by factor of two in each direction • Re sampled onto Bayer array and CFA interpolated Collected 100 images: 50 of resolution 512x512, 50 of resolution 1024x1024

  8. Gradient 3x3 median No CFA interpolation

  9. Results • Detecting Localized Tampering • Composite images – splicing the non CFA image and the same CFA interpolated image • Plausible forgery created using Adobe Photoshop

  10. Sensitivity and Robustness • Tested the sensitivity of the model to typical distortions that may conceal trace of tampering • JPEG compression, additive white Gaussian noise, Gamma correction • Robustness • Measure of similarity between probability maps of each color channel vs. synthetically generated probability maps Results: bilinear, bicubic, smooth hue, variable number of gradient - 100%, Median 99%, ACP 97%

  11. Discussion Advantages • The technique works in the absence of any digital watermark or signature • Simple linear model to capture the correlation produced by CFA interpolation • Shown efficacy Drawbacks • Can be attacked by resampleing onto CFA and then reinterpolating - requires knowledge of camera CFA pattern

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