3DKMI: A MATLAB package to generate shape signatures from Krawtchouk moments and an application to species delimitation in planktonic foraminifera

Abstract

Abstract The rapid and repeatable characterization of individual morphology has advanced automated taxonomic classification. The most direct study of evolutionary processes is, however, not from taxonomic description, but rather of the evolution of the traits that comprise individuals and define species. Repeatable signatures of individual morphology are crucial for analysing the response to selection at scale, and thus tracking evolutionary trajectories through time and across species boundaries. Here, we introduce our 3DKMI—an open‐source MATLAB package designed for the study of morphology using three‐dimensional (3D) Krawtchouk moment invariants. The volumetric features derived from the 3D images remain stable under translation, scaling and rotation and, for an image of size 128 × 128 × 128 can be computed in less than 0.1 s. We applied our package as a case study on a collection of 300 X‐ray computed tomography scans of planktonic foraminifera specimens across five species to (1) assess the invariance of the features under different transformations and (2) analyse morphological differences among species based on the extracted characteristics. We show that 3DKMI has the capacity to efficiently and repeatedly characterize the signatures of individual morphology. In the future, we hope that the 3D feature extraction technique 3DKMI will be widely applied to digital collections to advance research in ecology and evolution.

Keywords

• 3D Krawtchouk moments
• classification
• computer vision
• feature extraction
• machine learning
• planktonic foraminifera