Extending morphological pattern segmentation to 3D voxels
| dc.contributor.author | Remmel, Tarmo K | |
| dc.date.accessioned | 2023-03-10T17:38:30Z | |
| dc.date.available | 2023-03-10T17:38:30Z | |
| dc.date.issued | 2022-01 | |
| dc.description.abstract | This short communication introduces the logic, demonstrates its use, and identifies the availability of a new tool that extends the traditional 2D morphological segmentation of binary raster data into the 3-dimensional realm of voxels. A combination of 3-dimensional array data and network graph theory are implemented to facilitate the logical parsing of identified 3-dimensional features into their mutually exclusive constituent morphological classes. All processing is performed in the R environment, providing the ability for anyone to perform the demonstrated analyses on their own data. The only input requirement is a binary (1 = feature of interest, 0 otherwise) 3-dimensional array, where each voxel of interest is then classified into classes called outside, mass, skin, crumb, antenna, circuit, bond, and void that correspond their 2-dimensional equivalents of background, core, edge, islet, branch, loop, bridge, and perforation. An additional class called the void-volume identifies voxels belonging to the empty space within the object of interest. The work helps to bring pattern metrics into the 3-dimensional world, particularly given the reliance on adjacency and connectivity assessments | en_US |
| dc.description.sponsorship | Natural Sciences and Engineering Research Council (NSERC) Discovery Grant (RGPIN-2021-03645) | en_US |
| dc.identifier.citation | Remmel, T.K. 2022. Extending morphological pattern analysis to 3D voxels. Landscape Ecology 37(2):373-380. | en_US |
| dc.identifier.uri | 10.1007/s10980-021-01384-7 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10315/40904 | |
| dc.language.iso | en | en_US |
| dc.publisher | Springer | en_US |
| dc.rights | https://www.springernature.com/gp/open-research/policies/journal-policies "Where articles are published via the subscription route, Springer Nature permits authors to self-archive the accepted manuscript (AM), on their own personal website and/or in their funder or institutional repositories, for public release after an embargo period (see the table below). The accepted manuscript is the version post-peer review, but prior to copy-editing and typesetting, and does not reflect post-acceptance improvements, or any corrections. " | en_US |
| dc.rights | Attribution-NonCommercial-ShareAlike 4.0 International | * |
| dc.rights.article | https://link.springer.com/epdf/10.1007/s10980-021-01384-7?sharing_token=OHF_mmfn6K0mN0f_WVxWNfe4RwlQNchNByi7wbcMAY7dZUb7m4c7XZKm28LlVpRRy95kGv2vCYiuKPRiw5jpfGfJkQ1hRZqiVF8vb1-FGBKvSLt6AohNh6f4HbRoQaG0TMuqgr6FMMeVI94U7RlZ53vn8N99HgWmSi2QMLUEVfA%3D | en_US |
| dc.rights.journal | https://www.springer.com/journal/10980 | en_US |
| dc.rights.publisher | https://www.springer.com/us | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | * |
| dc.subject | Morphology | en_US |
| dc.subject | Landscape pattern | en_US |
| dc.subject | 3D segmentation | en_US |
| dc.subject | Volumetric data | en_US |
| dc.subject | Landscape structure | en_US |
| dc.title | Extending morphological pattern segmentation to 3D voxels | en_US |
| dc.type | Research Paper | en_US |
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