2005
DOI: 10.2225/vol8-issue3-fulltext-1
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Comparison of shape analysis methods for Guinardia citricarpa ascospore characterization

Abstract: Among the diseases affecting the commercial citrus production, the citrus black spot (CBS) is considered to cause substantial losses. The analyses of particles in suspension in the orchards and collected into a disc have been applied as a preventive action trying to identify the presence of fungus spores before symptom appearance. In this paper, we show the results of several shape analysis methods applied to the fungus, the first step to the aimed computer aided vision system, capable to assist the identifica… Show more

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Cited by 8 publications
(7 citation statements)
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“…In order to fully characterise this transition from spore to hypha, a means of distinguishing between these different objects is required. Boundary shape descriptors [48,49] could be utilised in conjunction with the morphological thresholds used in the current study to this end. A means of breaking up clumps of spores in the inoculum, such as sonication, may also help to alleviate the problem.…”
Section: Discussionmentioning
confidence: 99%
“…In order to fully characterise this transition from spore to hypha, a means of distinguishing between these different objects is required. Boundary shape descriptors [48,49] could be utilised in conjunction with the morphological thresholds used in the current study to this end. A means of breaking up clumps of spores in the inoculum, such as sonication, may also help to alleviate the problem.…”
Section: Discussionmentioning
confidence: 99%
“…Pazoti et al (2005), referring to a paper by Goes (2002), stated that -ascospores are spread not only on short, but also on long distances: the wind can spread it, infecting orchards at kilometres of distance‖. The pycnidiospores are formed into asexual fruiting bodies (pycnidia) on lesions in fruit, twigs and leaf litter.…”
Section: Spread By Natural Meansmentioning
confidence: 99%
“…We only use the magnitude (real part) of the coefficients. From those vectors we get the fibers high‐frequency values since they contain most of the information about finer details of the fibers shape [PGD*05]. In our examples, the resulting features are 30‐dimensional vectors, 10 from each component.…”
Section: Improved Projection Based Approach For the Analysis Of Fimentioning
confidence: 99%