Otary gets even smarter with the addition of 17 binarization methods now available!
I am thrilled to share a new update to Otary, my open-source Python library dedicated to image manipulation and 2D geometry processing.
Otary now includes 17 binarization methods, designed to make experimentation both simple for beginners and powerful for advanced users.
5 basic methods: easily accessible for quick and efficient use: simple, otsu, adaptive, bradley, and sauvola.
These methods are the most classic and effective, perfect for new users and for 90% of practical cases.
12 advanced methods: for users who want to explore, compare, and understand more sophisticated approaches.
They are intended for image processing specialists and researchers who want to experiment with new ideas.
The documentation presents a summary table of the 17 methods, classified by year of publication and accompanied by links to the original scientific articles.
In particular for converting scanned documents to black and white. Though you can get nicer results with grayscale.
This library might have saved me a lot of time recently, as I don't have a working scanner and was forced to photograph and clean up a lot of pages of documents. I used gimp, which required a lot of experimentation. It's only got a couple adaptive tools that can do the job with uneven lighting, but they sometimes require some pre or post processing for good results.
Consider including images showing the impact of the various methods.
Otary gets even smarter with the addition of 17 binarization methods now available!
I am thrilled to share a new update to Otary, my open-source Python library dedicated to image manipulation and 2D geometry processing.
Otary now includes 17 binarization methods, designed to make experimentation both simple for beginners and powerful for advanced users.
5 basic methods: easily accessible for quick and efficient use: simple, otsu, adaptive, bradley, and sauvola.
These methods are the most classic and effective, perfect for new users and for 90% of practical cases.
12 advanced methods: for users who want to explore, compare, and understand more sophisticated approaches. They are intended for image processing specialists and researchers who want to experiment with new ideas.
The documentation presents a summary table of the 17 methods, classified by year of publication and accompanied by links to the original scientific articles.
What is binarization used for? Scanning QR codes?
In particular for converting scanned documents to black and white. Though you can get nicer results with grayscale.
This library might have saved me a lot of time recently, as I don't have a working scanner and was forced to photograph and clean up a lot of pages of documents. I used gimp, which required a lot of experimentation. It's only got a couple adaptive tools that can do the job with uneven lighting, but they sometimes require some pre or post processing for good results.
Love this, gonna take a look when I get home for some weekend hacking
in your experience, which binarization (adaptive or otherwise) do you often practically use?