Low-cost hyper-spectral imaging system using a linear variable bandpass filter for agritech applications

Shigeng Song, Des Gibson, Sam Ahmadzadeh, Hin On Chu, Barry Warden, Russell Overend, Fraser Macfarlane, Paul Murray, Stephen Marshall, Matt Aitkenhead, Damian Bienkowski, Russell Allison

Research output: Contribution to journalArticle

Abstract

Hyperspectral imaging for agricultural applications provides a solution for non-destructive, large-area crop monitoring. However, current products are bulky and expensive due to complicated optics and electronics. A linear variable filter was developed for implementation into a prototype hyperspectral imaging camera that demonstrates good spectral performance between 450 and 900 nm. Equipped with a feature extraction and classification algorithm, the proposed system can be used to determine potato plant health with ∼88% accuracy. This algorithm was also capable of species identification and is demonstrated as being capable of differentiating between rocket, lettuce, and spinach. Results are promising for an entry-level, low-cost hyperspectral imaging solution for agriculture applications.

Original languageEnglish
Pages (from-to)A167-A175
Number of pages9
JournalApplied Optics
Volume59
Issue number5
Early online date27 Jan 2020
DOIs
Publication statusPublished - 10 Feb 2020

Keywords

  • deposition monitoring
  • thin film devices
  • hyperspectral imaging

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  • Projects

    Datasets

    Hyperspectral Crop Camera Dataset

    Macfarlane, F. (Creator), Murray, P. (Creator) & Marshall, S. (Creator), University of Strathclyde, 5 Jul 2018

    Dataset

    Cite this

    Song, S., Gibson, D., Ahmadzadeh, S., On Chu, H., Warden, B., Overend, R., Macfarlane, F., Murray, P., Marshall, S., Aitkenhead, M., Bienkowski, D., & Allison, R. (2020). Low-cost hyper-spectral imaging system using a linear variable bandpass filter for agritech applications. Applied Optics, 59(5), A167-A175. https://doi.org/10.1364/AO.378269