Automatic diagnostic of Nosemiasis Infestation on honey bee using image processing

 

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Detalles Bibliográficos
Autores: Prendas-Rojas, Juan Pablo, Figueroa-Mata, Geovanni, Ramírez-Montero, Marianyela, Calderón-Fallas, Rafael Ángel, Ramírez-Bogantes, Melvin, Travieso-González, Carlos Manuel
Formato: artículo original
Fecha de Publicación:2018
Descripción:Bees pollinate a wide variety of plant species, including agricultural crops. It is estimated that about 30% of the food consumed by the world population is derived from crops pollinated by bees.Nosemiasis infestation is one of the leading causes of bee hive loss worldwide. The laboratory methods for the diagnosis of the level of infestation by this microsporidium are slow, expensive and require the presence of an expert for spore count. It is proposed the creation of an automatic, reliable and economical system of quantification of Nosema infestation from digital image processing.Using the techniques of image segmentation, object characterization and shape counting, the Cantwell and Hemocytometer techniques have been automatically reproduced. For the counting of spores, three descriptors were implemented: size, eccentricity and circularity, in such a way that they are invariant to the scale and rotation of the images. We worked with a total of 375 photographs grouped in folders of 5, which were previously labeled according to the level of infestation (very mild, mild, moderate, semi-strong and strong). The correct diagnosis rate was 84%.
País:RepositorioTEC
Institución:Instituto Tecnológico de Costa Rica
Repositorio:RepositorioTEC
Lenguaje:Español
OAI Identifier:oai:repositoriotec.tec.ac.cr:2238/9903
Acceso en línea:https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/3621
https://hdl.handle.net/2238/9903
Palabra clave:Nosema; image segmentation; object count; image processing.
Nosema; segmentación de imágenes; conteo de objetos; procesamiento de imágenes.