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Data Publisher for Earth & Environmental Science

Schoening, Timm (2017): Source code for the Compact Morphology-based Nodule Delineation (CoMoNoD) algorithm. PANGAEA, https://doi.org/10.1594/PANGAEA.875070, Supplement to: Schoening, Timm; Jones, Daniel O B; Greinert, Jens (2017): Compact-Morphology-based poly-metallic Nodule Delineation. Scientific Reports, 7(1), https://doi.org/10.1038/s41598-017-13335-x

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Abstract:
This is the demonstration code for the "Compact Morphology-based Nodule Delineation" (CoMoNoD) algorithm.
CoMoNoD is a rapid method to delineate poly-metallic (or manganese) nodules from vertical benthic images. The paper describing the algorithm is currently under review. This algorithm makes extensive use of the OpenCV library for image processing and uses NVIDIA CUDA for computational speedup.
Related to:
Gazis, Iason-Zois; Schoening, Timm; Alevizos, Evangelos; Greinert, Jens (2018): Quantitative mapping and predictive modeling of Mn nodules' distribution from hydroacoustic and optical AUV data linked by random forests machine learning. Biogeosciences, 15(23), 7347-7377, https://doi.org/10.5194/bg-15-7347-2018
Peukert, Anne; Schoening, Timm; Alevizos, Evangelos; Köser, Kevin; Kwasnitschka, Tom; Greinert, Jens (2018): Understanding Mn-nodule distribution and evaluation of related deep-sea mining impacts using AUV-based hydroacoustic and optical data. Biogeosciences, 15(8), 2525-2549, https://doi.org/10.5194/bg-15-2525-2018
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