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Low-cost, high-volume imaging for entomological digitization.

Dirk Steinke1, Jaclyn T A McKeown1, Allison Zyba1

  • 1Centre for Biodiversity Genomics, University of Guelph, 50 Stone Road East, Guelph, Ontario, N1G 2W1, Canada University of Guelph Guelph Canada.

Zookeys
|July 22, 2024
PubMed
Summary

Digitizing natural history collections is now easier with a new, low-cost automated imaging system. This technique uses a computer numerical control (CNC) rig to rapidly capture high-resolution images of arthropod specimens.

Keywords:
AIArthropodacollectionsdatabasesinsectsmachine learningphotography

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Area of Science:

  • Natural History
  • Museum Studies
  • Digital Imaging Technology

Background:

  • Large-scale digitization of natural history collections necessitates automated image acquisition and processing.
  • Existing imaging systems are often complex and costly, limiting their widespread adoption.
  • There is a need for accessible and efficient methods for imaging museum specimens.

Purpose of the Study:

  • To develop a simple and inexpensive automated system for imaging medium-to-large arthropod specimens.
  • To create a high-throughput imaging solution for natural history collections.

Main Methods:

  • A digital SLR camera was mounted on a computer numerical control (CNC) motor-drive rig.
  • The system was designed for automated z-axis stacking to capture high-resolution images.
  • Assembly cost was targeted below $1000 USD (excluding the camera).

Main Results:

  • The system successfully captured high-resolution z-axis stacked images (6960 × 4640 pixels) of arthropod specimens larger than 5 mm.
  • The automated rig imaged 95 specimens in just 30 minutes, demonstrating high production capacity.
  • The total cost for the system, excluding a camera, was approximately $1000 USD.

Conclusions:

  • This simple, inexpensive CNC-based imaging system offers a practical solution for the large-scale digitization of natural history collections.
  • The system's low cost, ease of setup, and high throughput make it suitable for widespread deployment.
  • Automated imaging is crucial for modern natural history collection management and accessibility.