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

• Published in: Applied optics (2004) 2020-02, Vol.59 (5), p.A167
• Main Authors: Song, Shigeng, Gibson, Des, Ahmadzadeh, Sam, Chu, Hin On, Warden, Barry, Overend, Russell, Macfarlane, Fraser, Murray, Paul, Marshall, Stephen, Aitkenhead, Matt, Bienkowski, Damian, Allison, Russell
• Format: Article
• Language: English
• Subjects: Algorithms; Bandpass filters; Biosensing Techniques - instrumentation; Biosensing Techniques - methods; Calibration; Crops, Agricultural - metabolism; Feature extraction; Hyperspectral imaging; Hyperspectral Imaging - instrumentation; Hyperspectral Imaging - methods; Light; Low cost; Membranes, Artificial; Microwaves; Niobium - chemistry; Optical Devices - economics; Oxides - chemistry; Oxygen - chemistry; Plant Leaves - metabolism; Plasma Gases - chemistry; Potatoes; Refractometry; Silicon - chemistry; Spectrum Analysis; Spinach; Surface Properties
• ISSN: 1559-128X; 2155-3165
• DOI: 10.1364/AO.378269

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.