cryptomeria


An optical micrographs of Cryptomeria japonica


This 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.

Kayoko Kobayashi

wvtool

Image Tools for Automated Wood Identification

cryptomeria function

num [1:1079, 1:1000, 1:4] 0.886 0.89 0.863 0.639 0.424 ...
 - attr(*, "bits.per.sample")= int 8
 - attr(*, "samples.per.pixel")= int 4
 - attr(*, "sample.format")= chr "uint"
 - attr(*, "planar.config")= chr "contiguous"
 - attr(*, "compression")= chr "none"
 - attr(*, "x.resolution")= num 72
 - attr(*, "y.resolution")= num 72
 - attr(*, "resolution.unit")= chr "inch"
 - attr(*, "orientation")= chr "top.left"
 - attr(*, "artist")= chr "DP"
 - attr(*, "date.time")= chr "2016:07:29 11:38:28"
 - attr(*, "color.space")= chr "RGB"

cryptomeria: Image Sample Dataset

Description

Usage

Arguments

Format

Source

References

Examples