The ZXing project is designed around the
if-you-fail-try-and-try-again principle. This principle works very
well for constant streaming images, such as those coming from a
Camera. The downside is that even seriously low success rates are
considered acceptable, since the success rate is stackable.
The common talk in this project is that:
'A failure to scan a particular image is not a bug'.
This principal works extremely well for mobile devices (where camera
is the principal source):
- it requires limited CPU, thus saving on battery.
- it works blazing fast, thus enabling low-end devices.
- 1 in 10 rate means a bar-code scanned in 1-2 seconds, which is acceptable
However for One-Shot-One-Kill ZXing does not cut it (as of yet).
I myself have dropped the idea to use ZXing to read codes from
scanned documents.
However! If you have more processing power you can apply distortions
to the images and weirdly enough enhance the success rate.
Common nudges include:
- Blur the image (various blur sizes)
- Sharpen the image (especially after a blur)
- Resize the image (scale down works very well)
- Rotate the image (±45°, ±90°, etc.)
If you have the CPU power to do that those are all automation-supported tasks.
2012/8/3 Pat Rice <
patrick...@gmail.com>:
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