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:	0.2.3
Depends:	R (≥ 3.2.3)
Imports:	R.utils, readbitmap, pracma, magick, OpenImageR
Suggests:	grid, ggplot2, scales, shiny, testthat, mockery, knitr, rmarkdown
Published:	2020-01-09
Author:	Stefan Mayer [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

Documentation:

Reference manual:	imagefluency.pdf
Vignettes:	introduction

Downloads:

Package source:	imagefluency_0.2.3.tar.gz
Windows binaries:	r-devel: imagefluency_0.2.3.zip, r-release: imagefluency_0.2.3.zip, r-oldrel: imagefluency_0.2.3.zip
macOS binaries:	r-release (arm64): imagefluency_0.2.3.tgz, r-oldrel (arm64): imagefluency_0.2.3.tgz, r-release (x86_64): imagefluency_0.2.3.tgz, r-oldrel (x86_64): imagefluency_0.2.3.tgz
Old sources:	imagefluency archive

Linking:

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