Abstract
In this chapter, methods for loading, manipulating, and saving image files in R are presented. Dimension reduction and clustering analysis are developed in order to visually represent a corpus of images in standard scatter plots.
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Notes
- 1.
- 2.
The formula for circular median is not too complex; if you want to avoid loading another library, the following:atan2(mean(sin(mat[1,]*2*pi)), mean(cos(mat[1,]*2*pi))) / (2*pi) can be used in place of the median.circular(…) call (it is actually much faster).
- 3.
For a detailed description and visualization of the underlying algorithm see [1].
- 4.
To improve the final image, we also permute the set 1:length(files) using the sample function. The order matters in this case because the later images are overplotted on the first images. The default order of the files is not as visually pleasing as a random permutation as the original ordering was sorted by size and category.
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Arnold, T., Tilton, L. (2015). Image Data. In: Humanities Data in R. Quantitative Methods in the Humanities and Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-20702-5_8
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DOI: https://doi.org/10.1007/978-3-319-20702-5_8
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