Identification of flying insects in the spatial, spectral, and time domains with focus on mosquito imaging
(2021) In Sensors 21(10).- Abstract
Insects constitute a very important part of the global ecosystem and include pollinators, disease vectors, and agricultural pests, all with pivotal influence on society. Monitoring and control of such insects has high priority, and automatic systems are highly desirable. While capture and analysis by biologists constitute the gold standard in insect identification, optical and laser techniques have the potential for high-speed detection and automatic identification based on shape, spectroscopic properties such as reflectance and fluorescence, as well as wing-beat frequency analysis. The present paper discusses these approaches, and in particular presents a novel method for automatic identification of mosquitos based on image analysis,... (More)
Insects constitute a very important part of the global ecosystem and include pollinators, disease vectors, and agricultural pests, all with pivotal influence on society. Monitoring and control of such insects has high priority, and automatic systems are highly desirable. While capture and analysis by biologists constitute the gold standard in insect identification, optical and laser techniques have the potential for high-speed detection and automatic identification based on shape, spectroscopic properties such as reflectance and fluorescence, as well as wing-beat frequency analysis. The present paper discusses these approaches, and in particular presents a novel method for automatic identification of mosquitos based on image analysis, as the insects enter a trap based on a combination of chemical and suction attraction. Details of the analysis procedure are presented, and selectivity is discussed. An accuracy of 93% is achieved by our proposed method from a data set containing 122 insect images (mosquitoes and bees). As a powerful and cost-effective method, we finally propose the combination of imaging and wing-beat frequency analysis in an integrated instrument.
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- author
- Sun, Yuting ; Lin, Yueyu ; Zhao, Guangyu and Svanberg, Sune LU
- organization
- publishing date
- 2021-05-02
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Image, Insects, Mosquito, Spectroscopy, Wing-beat frequency
- in
- Sensors
- volume
- 21
- issue
- 10
- article number
- 3329
- publisher
- MDPI AG
- external identifiers
-
- pmid:34064829
- scopus:85105720211
- ISSN
- 1424-8220
- DOI
- 10.3390/s21103329
- language
- English
- LU publication?
- yes
- id
- 7d00ba21-6d23-43c8-a24e-5f6ce279e9fd
- date added to LUP
- 2021-06-01 17:53:28
- date last changed
- 2024-06-15 11:57:16
@article{7d00ba21-6d23-43c8-a24e-5f6ce279e9fd,
abstract = {{<p>Insects constitute a very important part of the global ecosystem and include pollinators, disease vectors, and agricultural pests, all with pivotal influence on society. Monitoring and control of such insects has high priority, and automatic systems are highly desirable. While capture and analysis by biologists constitute the gold standard in insect identification, optical and laser techniques have the potential for high-speed detection and automatic identification based on shape, spectroscopic properties such as reflectance and fluorescence, as well as wing-beat frequency analysis. The present paper discusses these approaches, and in particular presents a novel method for automatic identification of mosquitos based on image analysis, as the insects enter a trap based on a combination of chemical and suction attraction. Details of the analysis procedure are presented, and selectivity is discussed. An accuracy of 93% is achieved by our proposed method from a data set containing 122 insect images (mosquitoes and bees). As a powerful and cost-effective method, we finally propose the combination of imaging and wing-beat frequency analysis in an integrated instrument.</p>}},
author = {{Sun, Yuting and Lin, Yueyu and Zhao, Guangyu and Svanberg, Sune}},
issn = {{1424-8220}},
keywords = {{Image; Insects; Mosquito; Spectroscopy; Wing-beat frequency}},
language = {{eng}},
month = {{05}},
number = {{10}},
publisher = {{MDPI AG}},
series = {{Sensors}},
title = {{Identification of flying insects in the spatial, spectral, and time domains with focus on mosquito imaging}},
url = {{http://dx.doi.org/10.3390/s21103329}},
doi = {{10.3390/s21103329}},
volume = {{21}},
year = {{2021}},
}