Reflected Light Microscopic Iron ore image dataset for iron ore characterization
The dataset contains two folders "IronOreRLM" and "Sample Images". The folder Sample Images contains few images from each of the grades included in the study and has total of 12 images. This folder is like an abstract of the full dataset and has been created for preview purpose. The IronOreRLM folder is main dataset containing a total of 563 reflected light microscopic (RLM) images of iron ores collected from various mines across India. These RLM images are a valuable source of information about the ores, providing insights into constituent elements, ore quality, structure, and more. Various analyses can be conducted on this dataset to extract meaningful information from the images. The primary goal of acquiring this dataset is to automate the chemical-extensive tasks in mineral processing by leveraging the capabilities of computer vision. While the research work associated with the dataset has been cited in this article, it does not limit the scope of the dataset.
Authors
- Shama Firdaus (ORCID: https://orcid.org/0000-0003-2157-9149)
- Prabodha Ranjan Sahoo (ORCID: https://orcid.org/0000-0002-1227-8005)
- Subrajeet Mohapatra (ORCID: https://orcid.org/0000-0002-6919-4734)
- Shamama Anwar (ORCID: https://orcid.org/0000-0002-2013-7181)
Institutions
- Birla Institute of Technology, Mesra (IN)
- Indian Institute of Technology Dhanbad (IN)
Publication Details
- Journal
- Data in Brief
- Published
- 2025-04-04
- DOI
- https://doi.org/10.1016/j.dib.2025.111540
- Citations
- 1
- Primary Topic
- Mineral Processing and Grinding
- Type
- article
- Field-Weighted Citation Impact
- 0.71
Funders
- Science and Engineering Research Board