Computer Vision

QED has developed novel algorithms for tackling a variety of challenging computer vision problems. Below are a few example case studies that are not confined by NDAs.

DARPA Shredder Challenge

The 2011 DARPA Shredder Challenge sought out technologies for the rapid deshredding of shredded documents, inspired by military scenarios in which shredded documents are acquired by boots on the ground, imaged at high-resolution, and sent back to be rapidly deciphered. Dr. Wu assembled a team with former JPL colleagues, dubbed the Herded Rappers — an anagram of “Paper Shredder” — that received an Honorable Mention and ranked 13th out of over 9000 teams. While many teams in the top ten resorted to manual human assembly (jigsaw puzzle enthusiasts) or Mechanical-Turk-style crowdsourcing solutions (UCSD), our team developed software and mathematical techniques for attacking this problem in an automated fashion on a desktop computer. The sequence of images directly showcase different steps of our procedure when executed on the first puzzle.

shredded document

shreds automatically segmented, aligned, and properly oriented

tool for matching shreds to most likely neighboring candidates, sorted by goodness-of-fit metric

deshredded document

Cell Segmentation

Cell biologists from a bioinformatics lab presented us with the problem of designing an image processing algorithm for the automated segmentation and geometric measurement of cells from slide images — a task formerly relegated to interns and manual labor. These images are heavily corrupted by artifacts and often suffer from suboptimal illumination conditions. The screenshots below showcase our algorithms at work.

original image

automated cell segmentation

iterating through cells

decomposition of segmentation algorithm