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

Dirk SteinkeJaclyn T A McKeownAllison ZybaJoschka McLeodCorey FengPaul D N Hebert
Published in: ZooKeys (2024)
Large-scale digitization of natural history collections requires automation of image acquisition and processing. Reflecting this fact, various approaches, some highly sophisticated, have been developed to support imaging of museum specimens. However, most of these systems are complex and expensive, restricting their deployment. Here we describe a simple, inexpensive technique for imaging arthropods larger than 5 mm. By mounting a digital SLR camera on a CNC (computer numerical control) motor-drive rig, we created a system that captures high-resolution z-axis stacked images (6960 × 4640 pixels) of 95 specimens in 30 minutes. This system can be assembled inexpensively ($1000 USD without a camera) and it is easy to set-up and maintain. By coupling low cost with high production capacity, it represents a solution for digitizing any natural history collection.
Keyphrases
  • low cost
  • high resolution
  • deep learning
  • convolutional neural network
  • high speed
  • mass spectrometry
  • machine learning