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Pixel-based classification method for detecting unhealthy regions in leaf images

dc.contributor.authorMadhogaria, Satish
dc.contributor.authorSchikora, Marek
dc.contributor.authorKoch, Wolfgang
dc.contributor.authorCremers, Daniel
dc.contributor.editorHeiß, Hans-Ulrich
dc.contributor.editorPepper, Peter
dc.contributor.editorSchlingloff, Holger
dc.contributor.editorSchneider, Jörg
dc.date.accessioned2018-11-27T09:59:56Z
dc.date.available2018-11-27T09:59:56Z
dc.date.issued2011
dc.description.abstractIn this paper, we present a pixel-based, discriminative classification algorithm for automatic detection of unhealthy regions in leaf images. The algorithm is designed to distinguish image pixels as belonging to one of the two classes: healthy and unhealthy. The task is solved in three steps. First, we perform segmentation to divide the image into foreground and background. In the second step, support vector machine (SVM) is applied to predict the class of each pixel belonging to the foreground. And finally, we do further refinement by neighborhood-check to omit all falsely-classified pixels from second step. The results presented in this work are based on a model plant (Arabidobsis thaliana), which forms the ideal basis for the usage of the proposed algorithm in biological researches concerning plant disease control mechanisms.en
dc.identifier.isbn978-88579-286-4
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/18795
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2011 – Informatik schafft Communities
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-192
dc.titlePixel-based classification method for detecting unhealthy regions in leaf imagesen
dc.typeText/Conference Paper
gi.citation.endPage482
gi.citation.publisherPlaceBonn
gi.citation.startPage482
gi.conference.date4.-7. Oktober 2011
gi.conference.locationBerlin
gi.conference.sessiontitleRegular Research Papers

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