Your browser doesn't support javascript.
loading
Identification of Flying Insects in the Spatial, Spectral, and Time Domains with Focus on Mosquito Imaging.
Sun, Yuting; Lin, Yueyu; Zhao, Guangyu; Svanberg, Sune.
Affiliation
  • Sun Y; Guangdong Provincial Key Laboratory of Optical Information Materials and Technology & Center for Optical and Electromagnetic Research, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China.
  • Lin Y; National Center for International Research on Green Optoelectronics, South China Normal University, Guangzhou 510006, China.
  • Zhao G; Guangdong Provincial Key Laboratory of Optical Information Materials and Technology & Center for Optical and Electromagnetic Research, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China.
  • Svanberg S; National Center for International Research on Green Optoelectronics, South China Normal University, Guangzhou 510006, China.
Sensors (Basel) ; 21(10)2021 May 11.
Article in En | MEDLINE | ID: mdl-34064829
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, 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.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Culicidae Type of study: Diagnostic_studies Limits: Animals Language: En Journal: Sensors (Basel) Year: 2021 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Culicidae Type of study: Diagnostic_studies Limits: Animals Language: En Journal: Sensors (Basel) Year: 2021 Type: Article Affiliation country: China