Evidence for a selective link between cooperation and individual recognition

Tumulty, James P.; Miller, Sara E.; Van Belleghem, Steven M.; Weller, Hannah I.; Jernigan, Christopher M.; Vincent, Sierra; Staudenraus, Regan J.; Legan, Andrew W.; Polnaszek, Timothy J.; Uy, Floria M.K.; Walton, Alexander; Sheehan, Michael J.

doi:10.1016/j.cub.2023.11.032

Cited by 5 publications

(2 citation statements)

References 113 publications

(135 reference statements)

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“…We mapped each original image to this colour palette using imposeColors and performed a whole-colourpattern PCA as in Example A (Figure 4d). The entire colour segmentation process in this case took 2-4 min and illustrated a northern to southern gradient of facial colour patterns in wasp populations (Tumulty et al, 2023).…”

Section: Example B: Batch-processing For Uniform Imagesmentioning

confidence: 93%

“…With a set of images taken under more controlled conditions, recolorize can batch process images. Here we show an example using twenty Polistes fuscatus (Fabricius 1793) social wasp face images (Figure 4a) used with permission from the original set of 267 in Tumulty et al, (2023). The goal of the original paper was to illustrate a latitudinal gradient of facial colour pattern diversity that may relate to social behaviour.…”

Section: Example B: Batch-processing For Uniform Imagesmentioning

confidence: 99%

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recolorize: An R package for flexible colour segmentation of biological images

Weller,

Hiller,

Lord

et al. 2024

Ecology Letters

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Colour pattern variation provides biological information in fields ranging from disease ecology to speciation dynamics. Comparing colour pattern geometries across images requires colour segmentation, where pixels in an image are assigned to one of a set of colour classes shared by all images. Manual methods for colour segmentation are slow and subjective, while automated methods can struggle with high technical variation in aggregate image sets. We present recolorize, an R package toolbox for human‐subjective colour segmentation with functions for batch‐processing low‐variation image sets and additional tools for handling images from diverse (high‐variation) sources. The package also includes export options for a variety of formats and colour analysis packages. This paper illustrates recolorize for three example datasets, including high variation, batch processing and combining with reflectance spectra, and demonstrates the downstream use of methods that rely on this output.

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Section: Example B: Batch-processing For Uniform Imagesmentioning

confidence: 93%

Section: Example B: Batch-processing For Uniform Imagesmentioning

confidence: 99%