imagefluency: Image Statistics Based on Processing Fluency


imagefluency is a simple R package for image fluency scores. The package allows to get scores for several basic aesthetic principles that facilitate fluent cognitive processing of images.

The main functions are:

Other helpful functions are:

The main author is Stefan Mayer.


You can install the current stable version from CRAN.


To download the latest development version from Github use the install_github function of the remotes package.

# install remotes if necessary
if (!require('remotes')) install.packages('remotes')
# install imagefluency from github

Optionally, if you have rmarkdown installed, you can also have your system build the the vignettes when downloading from GitHub.

# install from github with vignettes (needs rmarkdown installed)
remotes::install_github('stm/imagefluency', build_vignettes = TRUE)

Use the following link to report bugs/issues:

Example usage

# visual contrast
# example image file (from package): bike.jpg
bike_location <- system.file('example_images', 'bike.jpg', package = 'imagefluency')
# read image from file
bike <- img_read(bike_location)
# get contrast

# visual symmetry
# read image
rails <- img_read(system.file('example_images', 'rails.jpg', package = 'imagefluency'))
# get only vertical symmetry
img_symmetry(rails, horizontal = FALSE)


See the getting started vignette for a detailed introduction and the reference page for details on each function.

If you are analyzing a larger number of images, make sure to read the tutorial on how to analyze multiple images at once.


To cite imagefluency in publications use:

Mayer, S. (2024). imagefluency: Image Statistics Based on Processing Fluency. R package version 0.2.5. doi: 10.5281/zenodo.5614665

A BibTeX entry is:

  author       = {Stefan Mayer},
  title        = {imagefluency: Image Statistics Based on Processing Fluency},
  year         = 2024,
  version      = {0.2.5},
  doi          = {10.5281/zenodo.5614665},
  url          = {}


The img_complexity function relies on the packages R.utils and magick. The img_self_similarity function relies on the packages OpenImageR, pracma, and quadprog. The img_read function relies on the readbitmap package. The run_imagefluency shiny app depends on shiny.

Further references

To learn more about the different image fluency metrics, see the following publications:

Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.