Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/327832
Type: Artigo
Title: Toward An Automated Identification Of Anastrepha Fruit Flies In The Fraterculus Group (diptera, Tephritidae)
Toward an automated identification of Anastrepha fruit flies in the fraterculus group (Diptera, Tephritidae)
Author: Perre, P.
Faria, F. A.
Jorge, L. R.
Rocha, A.
Torres, R. S.
Souza-Filho, M. F.
Lewinsohn, T. M.
Zucchi, R. A.
Abstract: In this study, we assess image analysis techniques as automatic identifiers of three Anastrepha species of quarantine importance, Anastrepha fraterculus (Wiedemann), Anastrepha obliqua (Macquart), and Anastrepha sororcula Zucchi, based on wing and aculeus images. The right wing and aculeus of 100 individuals of each species were mounted on microscope slides, and images were captured with a stereomicroscope and light microscope. For wing image analysis, we used the color descriptor Local Color Histogram; for aculei, we used the contour descriptor Edge Orientation Autocorrelogram. A Support Vector Machine classifier was used in the final stage of wing and aculeus classification. Very accurate species identifications were obtained based on wing and aculeus images, with average accuracies of 94 and 95%, respectively. These results are comparable to previous identification results based on morphometric techniques and to the results achieved by experienced entomologists. Wing and aculeus images produced equally accurate classifications, greatly facilitating the identification of these species. The proposed technique is therefore a promising option for separating these three closely related species in the fraterculus group.
In this study, we assess image analysis techniques as automatic identifiers of three Anastrepha species of quarantine importance, Anastrepha fraterculus (Wiedemann), Anastrepha obliqua (Macquart), and Anastrepha sororcula Zucchi, based on wing and aculeus
Subject: Identification
Image Analysis
Machine Learning
Mosca-das-frutas
Entomologia
Análise de imagem
Aprendizado de máquina
Reconhecimento de padrões
Máquina de vetores de suporte
Country: Países baixos
Editor: Springer
Citation: Neotropical Entomology. Entomological Soc Brasil, v. 45, p. 554 - 558, 2016.
Rights: aberto
Fechado
Identifier DOI: 10.1007/s13744-016-0403-0
Address: https://link.springer.com/article/10.1007%2Fs13744-016-0403-0
Date Issue: 2016
Appears in Collections:IB - Artigos e Outros Documentos
IC - Artigos e Outros Documentos

Files in This Item:
File SizeFormat 
000386379200012.pdf516.58 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.