K. Karnani, J. Pepper, Y. Bakiş, X. Wang, H. Bart Jr., D. Breen and J. Greenberg, "Computational Metadata Generation Methods for Biological Specimen Image Collections," International Journal on Digital Libraries, Vol. 25, pp. 157-174, June 2024.
Abstract:
Metadata is a key data source for researchers seeking to apply machine
learning (ML) to the vast collections of digitized biological specimens
that can be found online. Unfortunately, the associated metadata is often
sparse and, at times, erroneous. This paper extends previous research
conducted with the Illinois Natural History Survey (INHS) collection
(7,244 specimen images) that uses computational approaches to analyze image
quality, and then automatically generates 22 metadata properties
representing the image quality and morphological features of the specimens.
In the research reported here, we demonstrate the extension of our initial
work to University of the Wisconsin Zoological Museum (UWZM) collection
(4,155 specimen images). Further, we enhance our computational methods in
four ways: 1) augmenting the training set, 2) applying contrast enhancement,
3) upscaling small objects, and 4) refining our processing logic. Together
these new methods improved our overall error rates from 4.6% to 1.1%. These
enhancements also allowed us to compute an additional set of 17 image-based
metadata properties. The new metadata properties provide supplemental
features and information that may also be used to analyze and classify the
fish specimens. Examples of these new features include convex area,
eccentricity, perimeter, skew, etc. The newly refined process further
outperforms humans in terms of time and labor cost, as well as accuracy,
providing a novel solution for leveraging digitized specimens with ML.
This research demonstrates the ability of computational methods to enhance
the digital library services associated with the tens of thousands of
digitized specimens stored in open-access repositories world-wide by
generating accurate and valuable metadata for those repositories.
