Detects all photos in the provided scans and extracts them to separate files. Used when digitizing a large collection of photographs.
The following scan:
Is split into 4 separate images:
Current release is created for Java 8 on Windows 10 64-bit. Tested with TIFF files scanned at 600DPI.
Make sure you have Java installed.
Download multicrop-scanned-photos-1.0.zip in the releases tab of Github.
Run multicrop-scanned-photos-example.bat to extract the 4 photos from example-in directory to the example-out directory.
To extract your own photos, simply place them in the example-in directory and run multicrop-scanned-photos-example.bat. Subdirectories will be recreated in the output directory. Alternatively you can change multicrop-scanned-photos-example.bat to use different directories
Edit multicrop-scanned-photos.properties to change options:
| Option | Valid values | Default | Description |
|---|---|---|---|
write-debug |
true/false | false | When true, creates a debug directory with all the steps in the process. Great when determining threshold |
write-rects |
true/false | false | When true, creates a rects directory with the original scans and the detected photos outlined in green. Great to quickly find any missing/wrongly cropped photos when working with a large amount of scans |
threshold |
int 0-255 | 200 | The threshold used to separate the background (white) from the foreground (photos). 200-220 seem to be good values |
ignore-edge |
positive int | 100 | Scanners can leave artifacts around the edges of scans. This is the number of pixels around the edge that are ignored. The default of 100 should be good |
postcrop |
positive int | 25 | Edges won't be perfect. Cut this amount of pixels from the edges of detected photos |
min-area-ratio |
float 0.0-1.0 | 0.05 | The minimum area of detected photos relative to the entire scan. Increase this if parts of photos are being extracted |
max-area-ratio |
float 0.0-1.0 | 0.9 | The maximum area of detected photos relative to the entire scan. |
- Crop
ignore-edgepixels around the edges - Add a white border of
ignore-edgepixels - Transform to greyscale
- Threshold according to
thresholdvalue - Detect contours
- Detect rects, compensating for the removed border in step 1 and cropping according to
postcrop - Export to separate files
Inspired by: https://github.com/polm/ndl-crop
Couldn't have done it without: https://opencv.org/
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