tesseract: Tesseract OCR
In tesseract: Open Source OCR Engine

Description Usage Arguments Details References Examples

Extract text from an image. Requires that you have training data for the language you are reading. Works best for images with high contrast, little noise and horizontal text.

ocr(image, engine = tesseract("eng"))

tesseract(language = NULL, datapath = NULL, options = NULL,
  cache = TRUE)

`image`	file path, url, or raw vector to image (png, tiff, jpeg, etc)
`engine`	a tesseract engine created with `tesseract()`
`language`	string with language for training data. Usually defaults to `eng`
`datapath`	path with the training data for this language. Default uses the system library.
`options`	a named list with tesseract engine options
`cache`	use a cached version of this training data if available

Tesseract uses training data to perform OCR. Most systems default to English training data. To improve OCR performance for other langauges you can to install the training data from your distribution. For example to install the spanish training data:

tesseract-ocr-spa (Debian, Ubuntu)
tesseract-langpack-spa (Fedora, EPEL)

On other platforms you can manually download training data from github and store it in a path on disk that you pass in the datapath parameter. Alternatively you can set a default path via the TESSDATA_PREFIX environment variable.

Tesseract training data

# Simple example
text <- ocr("http://jeroen.github.io/images/testocr.png")
cat(text)

# Roundtrip test: render PDF to image and OCR it back to text
library(pdftools)
library(tiff)

# A PDF file with some text
setwd(tempdir())
news <- file.path(Sys.getenv("R_DOC_DIR"), "NEWS.pdf")
orig <- pdf_text(news)[1]

# Render pdf to jpeg/tiff image
bitmap <- pdf_render_page(news, dpi = 300, numeric = TRUE)
tiff::writeTIFF(bitmap, "page.tiff")

# Extract text from images
out <- ocr("page.tiff")
cat(out)

engine <- tesseract(options = list(tessedit_char_whitelist = "0123456789"))