| Issue |
MATEC Web Conf.
Volume 370, 2022
2022 RAPDASA-RobMech-PRASA-CoSAAMI Conference - Digital Technology in Product Development - The 23rd Annual International RAPDASA Conference joined by RobMech, PRASA and CoSAAMI
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|---|---|---|
| Article Number | 07007 | |
| Number of page(s) | 10 | |
| Section | Pattern Recognition | |
| DOI | https://doi.org/10.1051/matecconf/202237007007 | |
| Published online | 01 December 2022 | |
Object segmentation of solid waste material for further semantic segmentation
Academy of Computer Science and Software Engineering, University of Johannesburg, South Africa
* waseem.shaikjee@gmail.com
* dvanderhaar@uj.ac.za
Recycling is crucial in reducing solid waste and pollution. An optical waste sorter can reduce the amount of solid waste pollution. To locate and segment the waste objects from the captured image data, waste object segmentation is needed. Waste object segmentation presents a complex problem due to the physical nature of solid waste in the wild. Using the TACO Dataset, this paper assesses object segmentation concerning solid waste object segmentation in the wild with engineered features. We apply a watershed and an ensemble segmentation technique and review the technique against the TACO dataset.
© The Authors, published by EDP Sciences, 2022
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