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Reconstructing Shredded Documents Nathan Figueroa
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Reconstructing Shredded Documents

Feb 25, 2016

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Reconstructing Shredded Documents. Nathan Figueroa. Example: Original. Example: Shredded. Example: Reconstructed. Motivation. Method. Isolate: K-Means Segmentation. Pick K cluster means at random Assign each pixel to the nearest mean Compute a new mean for each cluster - PowerPoint PPT Presentation
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Page 1: Reconstructing Shredded Documents

Reconstructing Shredded Documents

Nathan Figueroa

Page 2: Reconstructing Shredded Documents

Example: Original

Page 3: Reconstructing Shredded Documents

Example: Shredded

Page 4: Reconstructing Shredded Documents

Example: Reconstructed

Page 5: Reconstructing Shredded Documents

Motivation

Security

Counter Intelligence

Forensic Photography

Page 6: Reconstructing Shredded Documents

Method

Isolate Align Match Reassemble

Page 7: Reconstructing Shredded Documents

Isolate: K-Means Segmentation

1. Pick K cluster means at random

2. Assign each pixel to the nearest mean

3. Compute a new mean for each cluster

4. Repeat 2 and 3 until convergence

Page 8: Reconstructing Shredded Documents

Isolate: K-Means Segmentation

• Advantages– Easy to implement– Requires no user interaction– Works well on a variety of images

• Challenges– Noise in certain color spaces– Artifacts along edge

Page 9: Reconstructing Shredded Documents

Isolate: Connected Components

• A connected component is a subgraph where every vertex is connected by a path to every other vertex in the subgraph

0 0 0 0 0 0 0 1 1 0

1 1 1 0 0 0 0 1 1 0

0 1 1 0 1 1 0 1 1 0

0 1 1 0 1 1 0 0 1 1

0 0 1 0 1 1 0 0 1 1

0 0 0 0 0 1 0 0 0 0

Page 10: Reconstructing Shredded Documents

Align: Centroids

• Centroid is the geometric center of mass

Page 11: Reconstructing Shredded Documents

Align: Second Central Moments

• The second central moments are defined by

• A 2x2 covariance matrix can be constructed from the moments of each region

• The eigenvectors of the covariance matrix relate to the width and length of region

Page 12: Reconstructing Shredded Documents

0 0 0 0 0 0 0 1 1 0

1 1 1 0 0 0 0 1 1 0

0 1 1 0 1 1 0 1 1 0

0 1 1 0 1 1 0 0 1 1

0 0 1 0 1 1 0 0 1 1

0 0 0 0 0 1 0 0 0 0

Align: Second Central Moments

Page 13: Reconstructing Shredded Documents

Align: Rotation

• The dominant orientation of a chad is the orientation of the largest eigenvector

• An affine rotation is applied to each chad so all chads have the same orientation

Page 14: Reconstructing Shredded Documents

Match: Sum of Squared Difference

• Shape of edge• Edge histograms• Optical character recognition• Simple sum of squared difference

Page 15: Reconstructing Shredded Documents

Reassemble: Automatic Jigsaw

• Fully automated systems perform well on small, single-page, multicolor documents

• Top 5 DARPA Shredder Challenge leaders relied on human interaction for reassembly

• Winning team took over 300 man hours to partially reassemble five puzzles