imagefluency-package | R Documentation |
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) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1037/aca0000187")} and Mayer & Landwehr (2018) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.31219/osf.io/gtbhw")} for the theoretical background of the methods.
The main functions are:
img_contrast
to get the visual contrast of an
image
img_complexity
to get the visual complexity of
an image (equals 1 minus image simplicity)
img_self_similarity
to get the visual
self-similarity of an image
img_simplicity
to get the visual simplicity
of an image (equals 1 minus image complexity)
img_symmetry
to get the vertical and
horizontal symmetry of an image
img_typicality
to get the visual typicality
of a list of images relative to each other
Other helpful functions are:
img_read
wrapper function
to read images using readbitmap::read.bitmap
run_imagefluency
to launch a Shiny app
for an interactive demo of the main functions
rgb2gray
to convert images from
RGB into grayscale
Maintainer: Stefan Mayer stefan@mayer-de.com (ORCID)
Mayer, S. & Landwehr, J, R. (2018). Quantifying Visual Aesthetics Based on Processing Fluency Theory: Four Algorithmic Measures for Antecedents of Aesthetic Preferences. Psychology of Aesthetics, Creativity, and the Arts, 12(4), 399–431. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1037/aca0000187")}
Mayer, S. & Landwehr, J. R. (2018). Objective measures of design typicality. Design Studies, 54, 146–161. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.31219/osf.io/gtbhw")}
Useful links:
Report bugs at https://github.com/stm/imagefluency/issues/
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