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Please use this identifier to cite or link to this item: http://ri.uaemex.mx/handle20.500.11799/68630
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dc.contributor.authorASDRUBAL LOPEZ CHAUen_EU
dc.contributor.authorRAFAEL ROJAS HERNANDEZen_EU
dc.contributor.authorVALENTIN TRUJILLO MORAen_EU
dc.contributor.authorJAIR CERVANTES CANALESen_EU
dc.contributor.authorLISBETH RODRIGUEZ MAZAHUAen_EU
dc.contributor.authorFARID GARCIA LAMONTen_EU
dc.creatorASDRUBAL LOPEZ CHAU-
dc.creatorRAFAEL ROJAS HERNANDEZ-
dc.creatorVALENTIN TRUJILLO MORA-
dc.creatorJAIR CERVANTES CANALES-
dc.creatorLISBETH RODRIGUEZ MAZAHUA-
dc.creatorFARID GARCIA LAMONT-
dc.date2017-
dc.identifierhttp://hdl.handle.net/20.500.11799/68630-
dc.descriptionIn most of classic plant identification methods a dichotomous or multi-access key is used to compare characteristics of leaves. Some questions about if the analyzed leaves are lobed, unlobed, simple or compound need to be answered to identify plants successfully. However, very little attention has been paid to make an automatic distinction of leaves using such features. In this paper we first explore if incorporating prior knowledge about leaves (categorizing between lobed simple leaves, and the unlobed simple ones) has an effect on the performance of six classification methods. According to the results of experiments with more than 1,900 images of leaves from Flavia data set, we found that it is statically significant the relationship between such categorization and the improvement of the performances of the classifiers tested. Therefore, we propose two novel methods to automatically differentiate between lobed simple leaves, and the unlobed simple ones. The proposals are invariant to rotation, and achieve correct prediction rates greater than 98%.-
dc.languageeng-
dc.publisherSpringer International Publishing-
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.rightshttp://creativecommons.org/licenses/by-nc/4.0-
dc.source0302-9743-
dc.source978-3-319-63314-5-
dc.subjectleaf features-
dc.subjectmcnemar test-
dc.subjectplant identification-
dc.subjectinfo:eu-repo/classification/cti/7-
dc.titleLeaf Categorization Methods for Plant Identification-
dc.typebookPart-
dc.audiencestudents-
dc.audienceresearchers-
item.grantfulltextnone-
item.fulltextNo Fulltext-
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