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Giorgio Sironi, profile picture
Uploaded byGiorgio Sironi
ODP, PPTX1,747 views

Blind detection of image manipulation @ PoliMi

The document discusses various techniques for the blind detection of image manipulation without the use of digital watermarks. It outlines pixel-based, format-based, camera-based, physics-based, and geometric-based approaches. It focuses on the use of projective geometry tools and geometric-based techniques like analyzing the assumptions of manual text selection and rectification to known fonts or objects to detect tampering. Key steps involve finding keypoints with SIFT feature detection, matching keypoint pairs with RANSAC, and comparing rectified images to reference samples to judge manipulation.

Related topics:
Image Processing Techniques•
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Blind detection of image manipulation Giorgio Sironi, matr. 764852 Politecnico di Milano - Como, January 12th, 2011
Problem statement http://xkcd.com/331
Possible solutions Automated detection of tampering on non-watermarked images Pixel-based Format-based Camera-based Physics-based Geometric-based
Pixel-based techniques Detection of cloning, resampling , splicing
Format based techniques Double JPEG , JPEG quantization and blocking
Camera based techniques Chromatic aberration , sensor noise...
Physics-based Light direction (2D or 3D)
Geometric-based Sign manipulations Assumptions: manual selection, [known font]
What is a photograph? Camera executes a projective transformation ( homography ). We use projective geometry tools.
Math background Homegeneous coordinates: O is (0,0,1)... Or (0,0,2), or (0,0,3). (10, 15) is (10, 15, 1) or (20, 30, 2)
Planar homography: 3x3 matrix (linear transformation)
How do we estimate an homography?
How do we find the keypoints? SIFT: feature detection
RANSAC: matching of keypoints pairs
How do we judge a rectification? Comparison between (binary) rectified image and world sample(s)
It's an arm race Computer programs support projective geometry tools; do humans?