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/osf.io/gtbhw> for the theoretical background of the methods.

Version: 0.2.1
Depends: R (≥ 3.2.3)
Imports: R.utils, readbitmap, pracma, quadprog, magick, OpenImageR
Suggests: grid, ggplot2, scales, shiny, testthat, knitr, rmarkdown
Published: 2019-09-27
Author: Stefan Mayer ORCID iD [aut, cre]
Maintainer: Stefan Mayer <stefan at mayer-de.com>
BugReports: https://github.com/stm/imagefluency/issues
License: GPL-3
URL: https://stm.github.io/imagefluency
NeedsCompilation: no
Materials: README NEWS
CRAN checks: imagefluency results

Downloads:

Reference manual: imagefluency.pdf
Vignettes: introduction
Package source: imagefluency_0.2.1.tar.gz
Windows binaries: r-devel: imagefluency_0.2.1.zip, r-release: imagefluency_0.2.1.zip, r-oldrel: imagefluency_0.2.1.zip
OS X binaries: r-release: imagefluency_0.2.1.tgz, r-oldrel: imagefluency_0.2.1.tgz

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