Raster and Image Analysis

Introduction

Calculating GLCM Texture

Gray Level Co-Occurrence Matrix (Haralick et al. 1973) texture is a powerful image feature for image analysis. The glcm package provides a easy-to-use function to calculate such texutral features for RasterLayer objects in R.

library(glcm)
library(raster)

r <- raster("C:/Program Files/R/R-3.2.3/doc/html/logo.jpg")
plot(r)

enter image description here

Calculating GLCM textures in one direction

rglcm <- glcm(r, 
              window = c(9,9), 
              shift = c(1,1), 
              statistics = c("mean", "variance", "homogeneity", "contrast", 
                             "dissimilarity", "entropy", "second_moment")
              )

plot(rglcm)

enter image description here

Calculation rotation-invariant texture features

The textural features can also be calculated in all 4 directions (0°, 45°, 90° and 135°) and then combined to one rotation-invariant texture. The key for this is the shift parameter:

rglcm1 <- glcm(r, 
              window = c(9,9), 
              shift=list(c(0,1), c(1,1), c(1,0), c(1,-1)), 
              statistics = c("mean", "variance", "homogeneity", "contrast", 
                             "dissimilarity", "entropy", "second_moment")
              )

plot(rglcm1)

enter image description here

Mathematical Morphologies

The package mmand provides functions for the calculation of Mathematical Morphologies for n-dimensional arrays. With a little workaround, these can also be calculated for raster images.

library(raster)
library(mmand)

r <- raster("C:/Program Files/R/R-3.2.3/doc/html/logo.jpg")
plot(r)

At first, a kernel (moving window) has to be set with a size (e.g. 9x9) and a shape type (e.g. disc, box or diamond)

sk <- shapeKernel(c(9,9), type="disc")

Afterwards, the raster layer has to be converted into an array wich is used as input for the erode() function.

rArr <- as.array(r, transpose = TRUE)
rErode <- erode(rArr, sk)
rErode <- setValues(r, as.vector(aperm(rErode)))

Besides erode(), also the morphological functions dilate(), opening() and closing() can be applied like this.

plot(rErode)

Eroded R Logo



2016-07-25
2017-02-15
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