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- Su - "Binarization of Historical Document Images Using the Local Maximum and Minimum", 2010.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