A Cost-Effective In Situ Zooplankton Monitoring System Based on Novel Illumination Optimization.
dark-field imaging
genetic algorithm
illumination optimization
microscopic imaging
zooplankton monitoring
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
19 Jun 2020
19 Jun 2020
Historique:
received:
17
03
2020
revised:
04
06
2020
accepted:
16
06
2020
entrez:
25
6
2020
pubmed:
25
6
2020
medline:
5
3
2021
Statut:
epublish
Résumé
A cost-effective and low-power-consumption underwater microscopic imaging system was developed to capture high-resolution zooplankton images in real-time. In this work, dark-field imaging was adopted to reduce backscattering and background noise. To produce an accurate illumination, a novel illumination optimization scheme for the light-emitting diode (LED) array was proposed and applied to design a lighting system for the underwater optical imaging of zooplankton. A multiple objective genetic algorithm was utilized to find the best location of the LED array, which resulted in the specific illumination level and most homogeneous irradiance in the target area. The zooplankton imaging system developed with the optimal configuration of LEDs was tested with
Identifiants
pubmed: 32575543
pii: s20123471
doi: 10.3390/s20123471
pmc: PMC7348824
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : National Natural Science Foundation of China
ID : 41406112
Organisme : National Natural Science Foundation of China
ID : 41776110
Organisme : Natural Science Foundation of Shandong Province
ID : ZR2019BD066
Organisme : Two-Hundred Talents Plan of Yantai
ID : NA
Organisme : Taishan Scholar Project Special Funding
ID : ts20190962
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