Toward an Automated Identification of Anastrepha Fruit Flies in the fraterculus group (Diptera, Tephritidae)

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• 作者：P Perre ; F A Faria ; L R Jorge ; A Rocha ; R S Torres…
• 关键词：Identification ; image analysis ; machine learning ; taxonomy
• 刊名：Neotropical Entomology
• 出版年：2016
• 出版时间：October 2016
• 年：2016
• 卷：45
• 期：5
• 页码：554-558
• 全文大小：472 KB
• 刊物主题：Entomology; Agriculture; Life Sciences, general;
• 出版者：Springer US
• ISSN：1678-8052
• 卷排序：45

文摘

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.