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dc.contributor.authorSugiyama, Junjien
dc.contributor.authorKobayashi, Kayokoen
dc.contributor.alternative杉山, 淳司ja
dc.contributor.alternative小林, 加代子ja
dc.date.accessioned2016-12-28T07:54:42Z-
dc.date.available2016-12-28T07:54:42Z-
dc.date.issued2016-11-07-
dc.identifier.urihttp://hdl.handle.net/2433/217709-
dc.description.abstractThis tool, wood vision tool, is intended to facilitate preprocessing and analyzing 2-dimensional wood images toward automated recognition. The former includes some basics such as functions to RGB to grayscale, gray to binary, cropping, rotation(bilinear), median/mean/Gaussian filter, and Canny/Sobel edge detection. The latter includes gray level co-occurrence matrix (GLCM), Haralick parameters, local binary pattern (LBP), higher order local autocorrelation (HLAC), Fourier transform (radial and azimuthal integration), and Gabor filtering. The functions are intended to read data using 'readTIFF(x, info=T)' from 'tiff' package. The functions in this packages basically assumes the grayscale images as input data, thus the color images should be subjected to the function rgb2gray() before used for some other functions.en
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherJunji Sugiyama, Kayoko Kobayashien
dc.titlewvtool: Image Tools for Automated Wood Identificationen
dc.typesoftware-
dc.type.niitypeSoftware-
dc.identifier.spage1-
dc.identifier.epage22-
dc.textversionauthor-
dc.relation.urlhttps://cran.r-project.org/web/packages/wvtool/index.html-
dcterms.accessRightsopen access-
出現コレクション:学術雑誌掲載論文等

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