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ZENODO
Software . 2024
Data sources: ZENODO
ZENODO
Software . 2024
Data sources: Datacite
ZENODO
Software . 2024
Data sources: Datacite
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Image Processing Workflow for Filtering, Segmenting, and Characterizing DIgital Porous Media

Authors: Turhan, Cinar; Prodanovic, Masa;

Image Processing Workflow for Filtering, Segmenting, and Characterizing DIgital Porous Media

Abstract

This workflow is for purposes of filtering, segmenting, and geometrically characterizing porous media image datasets. Presented as a Jupyter Notebook, it contains algorithms to correct beam hardening, denoise, segment, and characterize images. The geometric characterization algorithm demonstrates the shapes of pores in the segmented dataset. The workflow can be run on a laptop or a computer cluster, the latter requiring suitable code modifications. Since it is a Jupyter Notebook, users can easily modify the code cells for specific rock types. Usage instructions are provided in the Jupyter Notebook. The workflow is developed for a supervised master's thesis C. Turhan, "Towards Scalable Data Model for Curation and Reusable Workflows for Porous Media Image Analysis," The University of Texas at Austin (2024), and is being used by the Digital Porous Media Research Group.

If you use this software, please cite it.

Related Organizations
Keywords

image_filtering, image_correction, image_processing, segmentation, porous_media_imaging, beam_hardening

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average