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dc.contributor.authorHaugum, Matias
dc.contributor.authorFragoso, Glaucia
dc.contributor.authorHenriksen, Marie Bøe
dc.contributor.authorZolich, Artur
dc.contributor.authorJohansen, Tor Arne
dc.date.accessioned2024-02-22T12:29:43Z
dc.date.available2024-02-22T12:29:43Z
dc.date.created2024-01-02T18:55:45Z
dc.date.issued2023
dc.identifier.issn0197-7385
dc.identifier.urihttps://hdl.handle.net/11250/3119359
dc.description.abstractThe process of collecting samples for traditional microscopic analyses can be costly and time-consuming. We present the design of an autonomous flow-through imaging (AFTI) system tailored for small unmanned surface vehicles (USVs). Called the ’AFTI-scope’, the design is built around readily available microscopy parts. A peristaltic pump is used to move a water sample through a channel slide, which is positioned beneath a magnifying objective. Stepper motors give accurate control of the stage position and focus. An RGB-microscope camera images continuously the suspended microorganisms and other particles as they flow through the channel. Moreover, by using a stepper motor to pan the stage, hyperspectral datacubes were captured using a push-broom hyperspectral camera fixed to one of the eyepiece tubes of the microscope, which provides spectra of the particles that can be useful for classification. To segment the images for later classification and identification, an image processing pipeline is employed to perform various manipulations on the images, such as removing any particles that may have become stuck, subtracting the background, and normalizing the images. The resulting data set is a prime candidate for segmentation and quantification of particles. After segmentation, the reduced data set can either be sent to a taxonomist for identification or fed into algorithms for classification. Tests from plankton net samples showed that the system is capable of imaging suspended particles with a resolution of 0.41 µm/pixel at flow rates up to 7.8 ml/min. For the given setup, an image size 1280x960 pixels provides the best trade-off between resolution and frame rate, producing the clearest pictures with the least amount of motion blur.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAutonomous Flow-Through RGB and Hyperspectral Imaging for Unmanned Surface Vehiclesen_US
dc.title.alternativeAutonomous Flow-Through RGB and Hyperspectral Imaging for Unmanned Surface Vehiclesen_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© Copyright 2023 IEEE - All rights reserved.en_US
dc.source.journalOCEANSen_US
dc.identifier.doihttps://doi.org/10.1109/OCEANSLimerick52467.2023.10244605
dc.identifier.cristin2219356
dc.relation.projectNorges forskningsråd: 325961en_US
dc.relation.projectNorges forskningsråd: 327670en_US
dc.relation.projectNorges forskningsråd: 315514en_US
dc.relation.projectNorges forskningsråd: 223254en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode0


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal