imagefluency: Image Statistics Based on Processing Fluency


imagefluency is an 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 devtools package.

# install devtools if necessary
if (!require("devtools")) install.packages("devtools")
# install imagefluency from github

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 package vignette for a detailled introduction (or type vignette("imagefluency", package = "imagefluency") into the R console) and the reference page for details on each function.


If you want to cite this package in a scientific journal or in any other context, run the following code in your R console:

utils::citation(package = "imagefluency")

There is currently a publication in preparation corresponding this package and the citation will be updated once it’s published.


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.