文章基本信息

标题：Computer-assisted image processing to detect spores from the fungus Pandora neoaphidis
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作者：Reinert Korsnes ; Karin Westrum ; Erling Fløistad 等
期刊名称：MethodsX
印刷版ISSN：2215-0161
电子版ISSN：2215-0161
出版年度：2016
卷号：3
页码：231-241
DOI：10.1016/j.mex.2016.03.011
语种：English
出版社：Elsevier
摘要：Abstract This contribution demonstrates an example of experimental automatic image analysis to detect spores prepared on microscope slides derived from trapping. The application is to monitor aerial spore counts of the entomopathogenic fungus Pandora neoaphidis which may serve as a biological control agent for aphids. Automatic detection of such spores can therefore play a role in plant protection. The present approach for such detection is a modification of traditional manual microscopy of prepared slides, where autonomous image recording precedes computerised image analysis. The purpose of the present image analysis is to support human visual inspection of imagery data – not to replace it. The workflow has three components: • Preparation of slides for microscopy. • Image recording. • Computerised image processing where the initial part is, as usual, segmentation depending on the actual data product. Then comes identification of blobs, calculation of principal axes of blobs, symmetry operations and projection on a three parameter egg shape space.
关键词：Biological control;Computerised spore detection;Pathogenic fungus