A rapid and cost-effective pipeline for digitization of museum specimens with 3D photogrammetry

Joshua J Medina, James M Maley, Siddharth Sannapareddy, Noah N Medina, Cyril M Gilman and John E McCormack

PLOS ONE, 2020, vol. 15, issue 8, 1-14

Abstract: Natural history collections are yielding more information as digitization brings specimen data to researchers, connects specimens across museums, and as new technologies allow for more large-scale data collection. Therefore, a key goal in specimen digitization is developing methods that both increase access and allow for the highest yield of phenomic data. 3D digitization is increasingly popular because it has the potential to meet both aspects of that key goal. However, current methods overlook or do not prioritize some of the most sought-after phenotypic traits, those involving the external appearance of specimens, especially color. Here, we introduce an efficient and cost-effective pipeline for 3D photogrammetry to capture the external appearance of natural history specimens and other museum objects. 3D photogrammetry aligns and compares sets of dozens, hundreds, or even thousands of photos to create 3D models. The hardware set-up requires little physical space and around $3,000 in initial investment, while the software pipeline requires $1,400/year for proprietary software subscriptions (with open-source alternatives). The creation of each 3D model takes 1–2 hours/specimen and much of the software pipeline is automated with minimal supervision required, including the onerous step of mesh processing. We showcase the method by creating 3D models for most of the type specimens in the Moore Laboratory of Zoology bird collection and show that digital bill measurements are comparable to hand-taken measurements. Color data, while not included as part of this pipeline, is easily extractable from the models and one of the most promising areas of data collection. Future advances can adapt the method for ultraviolet reflectance capture and increased efficiency and model quality. Combined with genomic data, phenomic data from 3D models including photogrammetry will open new doors to understanding organismal evolution.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0236417

DOI: 10.1371/journal.pone.0236417

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