Augmenting Polarized Light Microscopy with Computational Imaging and Deep Learning for Cultural Heritage

Project: Research project

Project Details

Description

The project proposed here builds on this significant infrastructure and know-how within the conservation profession on PLM use. Focusing on the extensive archive of pigment dispersion slides at the Art Institute of Chicago1 and the Forbes collection at Harvard Art Museums as source materials, this proposal aims to maximize the amount of information extracted from PLM through recent advances in sensor hardware combined with computational imaging and deep learning. In short, we will be modernizing PLM by “harnessing the data revolution”2 to provide cutting-edge resources for conservators to make pigment identifications and to diagnose patterns of deterioration. As a core part of our dissemination, we will be making both the data collected as well as software pipelines open source for use by anyone and accessible through the Center of Scientific Studies in the Arts’ (NU-ACCESS) online presence. A training resource, to be released in the last year of funding, will be developed with video tutorials, readings, and in-depth descriptions on the methods and tools described in this proposal and will provide a capstone to the project.
StatusActive
Effective start/end date3/1/222/28/25

Funding

  • National Endowment for the Humanities (PR-284405-22)

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