Abstract
With a great variety of shapes and sizes, compound eye morphologies give insight into visual ecology, development, and evolution, and inspire novel engineering. In contrast to our own camera-type eyes, compound eyes reveal their resolution, sensitivity, and field of view externally, provided they have spherical curvature and orthogonal ommatidia. Non-spherical compound eyes with skewed ommatidia require measuring internal structures, such as with MicroCT (μCT). Thus far, there is no efficient tool to characterize compound eye optics, from either 2D or 3D data, automatically. Here we present two open-source programs: (1) the ommatidia detecting algorithm (ODA), which measures ommatidia count and diameter in 2D images, and (2) a μCT pipeline (ODA-3D), which calculates anatomical acuity, sensitivity, and field of view across the eye by applying the ODA to 3D data. We validate these algorithms on images, images of replicas, and μCT eye scans from ants, fruit flies, moths, and a bee.
Competing Interest Statement
This research was supported by grants from the National Science Foundation: IOS-1750833 to JT, BCS-1525371 to JC, DEB-1557007 to AYK and JT and IOS-1920895 to AYK. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the National Science Foundation.
Footnotes
We added benchmark tests to compare the performance of the ODA and ODA-3D to manual measurements. We added several datasets to the results: SEM eye images of 5 individuals from 2 fruit fly species (D. melanogaster and D. mauritiana) and a microCT of a D. mauritiana eye. We replaced the bumblebee scan with a honeybee scan from the same experiment. Finally, we modified the text substantially and changed some of the in-depth analyses we did of the bee eye in favor of a more general and comparative approach.
