Poster + Paper
12 March 2024 Automating the purity analysis of oilseed rape through usage of hyperspectral imaging
Fabian Erichsmeier, Maksim Kukushkin, Johannes Fiedler, Matthias Enders, Simon Goertz, Martin Bogdan, Thomas Schmid, Reinhard Kaschuba
Author Affiliations +
Conference Poster
Abstract
The purity analysis of oilseed rape (Brassica napus L.) is currently a labor-intensive and manual process, requiring significant human effort for accurate assessment. In this context, the KIRa-Sorter system presents an innovative solution that leverages hyperspectral imaging technology for automating the comprehensive classification of various contaminants present in rapeseed samples. The initial phase of the KIRa-Sorter system involves the efficient capture of hyperspectral and RGB image data from rapeseed samples as input for classification. From up to 200 different types of foreign objects typically found in these samples, a reduced coreset has been defined that the system is able to automatically singulate, classify and physically sort.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Fabian Erichsmeier, Maksim Kukushkin, Johannes Fiedler, Matthias Enders, Simon Goertz, Martin Bogdan, Thomas Schmid, and Reinhard Kaschuba "Automating the purity analysis of oilseed rape through usage of hyperspectral imaging", Proc. SPIE 12879, Photonic Technologies in Plant and Agricultural Science, 128790E (12 March 2024); https://doi.org/10.1117/12.3002665
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KEYWORDS
Cameras

RGB color model

Hyperspectral imaging

Image classification

Artificial intelligence

Classification systems

Agriculture

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