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Su - “Binarization of Historical Document Images Using the Local Maximum and Minimum”, 2010.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