imagefluency: Image Statistics Based on Processing Fluency

Get image statistics based on processing fluency theory. The functions provide scores for several basic aesthetic principles that facilitate fluent cognitive processing of images: contrast, complexity / simplicity, self-similarity, symmetry, and typicality. See Mayer & Landwehr (2018) <doi:10.1037/aca0000187> and Mayer & Landwehr (2018) <doi:10.31219/> for the theoretical background of the methods.

Version: 0.2.5
Depends: R (≥ 4.1.0)
Imports: R.utils, readbitmap, pracma, magick, OpenImageR
Suggests: grid, ggplot2, scales, shiny, testthat, mockery, knitr, rmarkdown, furrr, future, pbmcapply, tictoc, dplyr
Published: 2024-02-22
DOI: 10.32614/CRAN.package.imagefluency
Author: Stefan Mayer ORCID iD [aut, cre]
Maintainer: Stefan Mayer <stefan at>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: imagefluency results


Reference manual: imagefluency.pdf
Vignettes: getting-started


Package source: imagefluency_0.2.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): imagefluency_0.2.5.tgz, r-oldrel (arm64): imagefluency_0.2.5.tgz, r-release (x86_64): imagefluency_0.2.5.tgz, r-oldrel (x86_64): imagefluency_0.2.5.tgz
Old sources: imagefluency archive


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