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Identification of flying insects in the spatial, spectral, and time domains with focus on mosquito imaging

Sun, Yuting ; Lin, Yueyu ; Zhao, Guangyu and Svanberg, Sune LU (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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Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
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
  • scopus:85105720211
  • pmid:34064829
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
2024-04-06 04:26:39
@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}},
}