Code and example images from: recolorize: An R package for flexible color segmentation of biological images

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dc.contributor.affiliationKU Leuven-Van Belleghem, Steven
dc.contributor.authorVan Belleghem, Steven
dc.date.accessioned2025-04-29T14:04:55Z
dc.date.issued2024-01-31
dc.date.issued2024-01-31
dc.descriptionColor pattern variation provides biological information in fields ranging from disease ecology to speciation dynamics. Comparing color pattern geometries across images requires color segmentation, where pixels in an image are assigned to one of a set of color classes shared by all images. Manual methods for color 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 color 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 color 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.
dc.identifierhttps://doi.org/10.5061/dryad.9kd51c5r3
dc.identifier.urihttps://datakatalogi.helsinki.fi/handle/123456789/6108
dc.rights.licensecc-zero
dc.subjectsoftware
dc.subjectcolor pattern
dc.subjectImage segmentation
dc.subjectR
dc.subjectcolor
dc.subjecttrait analysis
dc.titleCode and example images from: recolorize: An R package for flexible color segmentation of biological images
dc.typedataset

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