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MSI-RPi: Affordable, Portable, and Modular Multispectral Imaging Prototype Suited to Operate in UV, Visible and Mid-Infrared Regions
Örebro University, School of Science and Technology. (MRO LAB, Centre for Applied Autonomous Sensor Systems (AASS))ORCID iD: 0000-0003-1827-9698
Örebro University, School of Science and Technology. (MRO LAB, Centre for Applied Autonomous Sensor Systems (AASS))ORCID iD: 0000-0002-2953-1564
2022 (English)In: Journal of Mobile Multimedia, ISSN 1550-4646, E-ISSN 1550-4654, Vol. 18, no 3, p. 723-742Article in journal (Refereed) Published
Abstract [en]

Digital plant inventory provides critical growth insights, given the associated data quality is good. Stable & high-quality image acquisition is critical for further examination. In this work, we showcase an affordable, portable, and modular spectral camera prototype, designed with open hardware’s and open-source software’s. The image sensors used were color, and infrared Pi micro-camera. The designed prototype presents the advantage as being low-cost and modular with respect to other general commercial market available spectral devices. The micro-size connected sensors make it a compact instrument that can be used for any general spectral acquisition purposes, along with the provision of custom selection of the bands, making the presented prototype design a Plug-nd-Play (PnP) setup that can be used in different wide application areas. The images acquired from our custom-built prototype were back-tested by performing image analysis and qualitative assessments. The image acquisition software, and processing algorithm has been programmed, which is bundled with our developed system. Further, an end-to-end automation script is integrated for the users to readily leverage the services on-demand. The design files, schematics, and all the related materials of the spectral block design is open-sourced with open-hardware license & is made available at https://github.com/ajayarunachalam/Multi-Spectral-Imaging-RaspberryPi-Design. The automated data acquisition scripts & the spectral image analysis done is made available at https://github.com/ajayarunachalam/SI-RPi.

Place, publisher, year, edition, pages
River Publishers , 2022. Vol. 18, no 3, p. 723-742
Keywords [en]
imaging technology, low-cost, spectral, phenotype, plant science, vision, imaging sensors, agriculture, image analysis
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-97240DOI: 10.13052/jmm1550-4646.18312Scopus ID: 2-s2.0-85125836417OAI: oai:DiVA.org:oru-97240DiVA, id: diva2:1635462
Available from: 2022-02-07 Created: 2022-02-07 Last updated: 2022-04-22Bibliographically approved

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Arunachalam, AjayAndreasson, Henrik

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