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Automatically extract documents from images and perspectively correct them with classic computer-vision algorithms

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Perspectra

Software and corresponding workflow to scan documents and books with as little hardware as possible.

Check out github:adius/awesome-scanning for and extensive list of alternative solutions.

Usage

Command Line Interface

usage: perspectra [-h] [--debug] {binarize,correct,corners,renumber-pages} ...

options:
  -h, --help            show this help message and exit
  --debug               Render debugging view

subcommands:
  subcommands to handle files and correct photos

  {binarize,correct,corners,renumber-pages}
                        additional help
    binarize            Binarize image
    correct             Pespectively correct and crop photos of documents.
    corners             Returns the corners of the document in the image
                        as [top-left, top-right, bottom-right, bottom-left]
    renumber-pages      Renames the images in a directory according to their page numbers.
                        The assumend layout is `cover -> odd pages -> even pages reversed`

Best Practices for Taking the Photos

Your photos should ideally have following properties:

  • Photos with 10 - 20 Mpx
  • Contain 1 document
    • Rectangular
    • Pronounced corners
    • Only black content on white or light-colored paper
    • On dark background
    • Maximum of 30° rotation

Camera Settings

# Rule of thumb is the inverse of your focal length,
# but motion blur is pretty much the worst for readable documents,
# therefore use at least half of it and never less than 1/50.
shutter: 1/50 - 1/200 s

# The whole document must be sharp even if you photograph it from an angle.
# Therefore at least 8 f.
aperture: 8-12 f

# Noise is less bad than motion blur => relative high ISO
# Should be the last thing you set:
# As high as necessary as low as possible
iso: 800-6400

When using Tv (Time Value) or Av (Aperture Value) mode use exposure compensation to set lightness value below 0. You really don't want to overexpose your photos as the bright pages are the first thing that clips.

On the other hand, it doesn't matter if you loose background parts because they are to dark.

Generating the Photos from a Video

A good tool for this purpose is PySceneDetect. It's a Python/OpenCV-based scene detection program, using threshold/content analysis on a given video.

For easy installation you can use the docker image

Find good values for threshold:

docker run \
  --rm \
  --volume (pwd):/video \
  handflucht/pyscenedetect
  --input /video/page-turning.mp4 \
  --downscale-factor 2 \
  --detector content \
  --statsfile page-turning-stats.csv

To launch the image run:

docker run \
  --interactive \
  --tty \
  --volume=(pwd):/video \
  --entrypoint=bash \
  handflucht/pyscenedetect

Then run in the shell:

cd /video
scenedetect \
  --input page-turning.mp4 \
  --downscale-factor 2 \
  --detector content \
  --threshold 3 \
  --min-scene-length 80 \
  --save-images

TODO: The correct way to do this: (after Breakthrough/PySceneDetect#45 is implemented)

docker run \
  --rm \
  --volume (pwd):/video \
  handflucht/pyscenedetect \
  --input /video/page-turning.mp4 \
  --downscale-factor 2 \
  --detector content \
  --threshold 3 \
  --min-scene-length 80 \
  --save-images <TODO: path>

Aim for a low threshold and a long minimun scene length. I.e. turn the page really fast and show it for a long time.

TODO