| Type: | Package |
| Title: | Binarize Images for Enhancing Optical Character Recognition |
| Version: | 0.1.3 |
| Maintainer: | Jan Wijffels <jwijffels@bnosac.be> |
| Description: | Improve optical character recognition by binarizing images. The package focuses primarily on local adaptive thresholding algorithms. In English, this means that it has the ability to turn a color or gray scale image into a black and white image. This is particularly useful as a preprocessing step for optical character recognition or handwritten text recognition. |
| License: | MPL-2.0 |
| URL: | https://github.com/DIGI-VUB/image.binarization |
| Encoding: | UTF-8 |
| Depends: | R (≥ 4.0.0) |
| Imports: | Rcpp, magick, grDevices |
| LinkingTo: | Rcpp |
| RoxygenNote: | 7.1.2 |
| SystemRequirements: | C++17 |
| NeedsCompilation: | yes |
| Packaged: | 2022-08-17 08:41:10 UTC; jwijffels |
| Author: | Jan Wijffels [aut, cre, cph] (R wrapper), Vrije Universiteit Brussel - DIGI: Brussels Platform for Digital Humanities [cph] (R wrapper), Brandon M. Petty [ctb, cph] (Files in src/Doxa) |
| Repository: | CRAN |
| Date/Publication: | 2022-08-17 10:50:09 UTC |
Binarize Images For Enhancing Optical Character Recognition
Description
Binarize images in order to further process it for Optical Character Recognition (OCR) or Handwritten Text Recognition (HTR) purposes
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Su - "Binarization of Historical Document Images Using the Local Maximum and Minimum", 2010.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.
Usage
image_binarization(x, type, opts = list())
Arguments
x |
an image of class 'magick-image'. In grayscale. E.g. a PGM file. If not provided in grayscale, will extract the gray channel. |
type |
a character string with the type of binarization to use. Either 'otsu', 'bernsen', 'niblack', 'sauvola', 'wolf', 'nick', 'gatos', 'su', 'trsingh', 'bataineh', 'wan' or 'isauvola' |
opts |
a list of options to pass on to the algorithm. See the details and the examples. |
Details
Options which can be bassed on to the binarization routines, with the defaults between brackets
otsu: none
bernsen: window(75L), k(0.2), threshold(100L), contrast-limit(25L)
niblack: window(75L), k(0.2)
sauvola: window(75L), k(0.2)
wolf: window(75L), k(0.2)
nick: window(75L), k(-0.2)
gatos: window(75L), k(0.2), glyph(60L)
su: window(75L), minN(75L)
trsingh: window(75L), k(0.2)
bataineh: none
wan: window(75L), k(0.2)
isauvola: window(75L), k(0.2)
Note that it is important that you provide the window / threshold / contrast-limit, minN, glyph argument as integers (e.g. as in 75L) and the other parameters as numerics.
Value
a binarized image of class magick-image as handled by the magick R package
Examples
library(magick)
f <- system.file("extdata", "doxa-example.png", package = "image.binarization")
img <- image_read(f)
img <- image_convert(img, format = "PGM", colorspace = "Gray")
binary <- image_binarization(img, type = "otsu")
binary
binary <- image_binarization(img, type = "bernsen",
opts = list(window = 50L, k = 0.2, threshold = 50L))
binary
binary <- image_binarization(img, type = "niblack", opts = list(window = 75L, k = 0.2))
binary
binary <- image_binarization(img, type = "sauvola")
binary
binary <- image_binarization(img, type = "wolf")
binary
binary <- image_binarization(img, type = "nick", opts = list(window = 75L, k = -0.2))
binary
binary <- image_binarization(img, type = "gatos", opts = list(window = 75L, k = 0.2, glyph = 50L))
binary
binary <- image_binarization(img, type = "su", opts = list(window = 20L))
binary
binary <- image_binarization(img, type = "trsingh")
binary
binary <- image_binarization(img, type = "bataineh")
binary
binary <- image_binarization(img, type = "wan")
binary
binary <- image_binarization(img, type = "isauvola", opts = list(window = 75L, k = 0.2))
binary