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image.binarization
This repository contains an R package for Binarizing Images focusing
on local adaptive thresholding with the purpose of improving
Optical Character Recognition (OCR)
Handwritten Text Recognition (HTR)
Installation
For regular users, install the package from your local CRAN mirror
install.packages("image.binarization")
For installing the development version of this package:
remotes::install_github("DIGI-VUB/image.binarization")
Note that the package requires a compiler with C++17
capabilities
Look to the documentation of the functions
help(package = "image.binarization")
Example
Get an image, put it into gray scale and binarise it using the method
by Su
library(magick)
library(image.binarization)
img <- image_read("scan.jpg")
img <- image_convert(img, format = "PGM", colorspace = "Gray")
img
img <- image_binarization(img, type = "su")
img
Algorithms
Otsu - “A threshold selection method from gray-level histograms”,
1979.
Bernsen - “Dynamic thresholding of gray-level images”, 1986.
Niblack - “An Introduction to Digital Image Processing”, 1986.
Sauvola - “Adaptive document image binarization”, 1999.
Wolf - “Extraction and Recognition of Artificial Text in Multimedia
Documents”, 2003.
Gatos - “Adaptive degraded document image binarization”, 2005.
(Partial)
NICK - “Comparison of Niblack inspired Binarization methods for
ancient documents”, 2009.
Su - “Binarization of Historical Document Images Using the Local
Maximum and Minimum”, 2010.
T.R. Singh - “A New local Adaptive Thresholding Technique in
Binarization”, 2011.
Bataineh - “An adaptive local binarization method for document
images based on a novel thresholding method and dynamic windows”, 2011.
(unreproducible)
ISauvola - “ISauvola: Improved Sauvola’s Algorithm for Document
Image Binarization”, 2016.
WAN - “Binarization of Document Image Using Optimum Threshold
Modification”, 2018.
Based on https://github.com/brandonmpetty/Doxa
DIGI
By DIGI: Brussels Platform for Digital Humanities:
https://digi.research.vub.be