MSI-RPi: Affordable, Portable, and Modular Multispectral Imaging Prototype Suited to Operate in UV, Visible and Mid-Infrared Regions

Authors

  • Ajay Arunachalam MRO LAB, Centre for Applied Autonomous Sensor Systems (AASS), Örebro University, Örebro, Sweden https://orcid.org/0000-0003-1827-9698
  • Henrik Andreasson MRO LAB, Centre for Applied Autonomous Sensor Systems (AASS), Örebro University, Örebro, Sweden

DOI:

https://doi.org/10.13052/jmm1550-4646.18312

Keywords:

imaging technology, low-cost, spectral, phenotype, plant science, vision, imaging sensors, agriculture, image analysis

Abstract

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.

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Author Biographies

Ajay Arunachalam, MRO LAB, Centre for Applied Autonomous Sensor Systems (AASS), Örebro University, Örebro, Sweden

Ajay Arunachalam works as a researcher at the Centre for Applied Autonomous Sensor Systems (AASS), School of Science and Technology, Örebro University, Örebro, Sweden. His research areas include Machine Learning/Deep Learning, Opacity in AI systems, Optimization, Big Data, Computer Vision, NLP, and Distributed Systems & Wireless Networks.

Henrik Andreasson, MRO LAB, Centre for Applied Autonomous Sensor Systems (AASS), Örebro University, Örebro, Sweden

Henrik Andreasson is an associate professor at the Centre for Applied Autonomous Sensor Systems (AASS), School of Science and Technology, Örebro University, Örebro, Sweden. He pursued his master’s from the Royal Institute of Technology (KTH), Stockholm, in 2001 and got his Ph.D. in computer science from Örebro University, in 2008. His research works are in mobile robotics, computer vision, and machine learning areas.

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Published

2022-02-04

How to Cite

Arunachalam, A. ., & Andreasson, H. . (2022). MSI-RPi: Affordable, Portable, and Modular Multispectral Imaging Prototype Suited to Operate in UV, Visible and Mid-Infrared Regions. Journal of Mobile Multimedia, 18(03), 723–742. https://doi.org/10.13052/jmm1550-4646.18312

Issue

Section

Computer Vision and its Application in Agriculture