RTextureMetrics (version 1.1)

genGLCM: genGLCM (generate GLC-Matrix)

Description

genGLCM generates a Grey Level Co-occurrence Matrix (GLCM)

Usage

genGLCM(direction, distance, rawmat)

Arguments

direction

assigns the direction of the neighbour (1=east, right), (2=south, down), (3=west, left), (4=north, up)

distance

assigns the number of pixels between reference and neighbour

rawmat

assigns the grey level [0..255] pixel matrix of a picture

Value

• returns a normalized propability matrix of the occurrence of different grey values

Details

GLCM is a tabulation of how often different combinations of pixel brightness values (grey levels) occur in an image.

References

Toennies, D., 2005: Grundlagen der Bildverarbeitung. Pearson Studium, 341 S. Harralick, R.M., Shanmugam, K., Dinstein, I., 1973: Textural Features for image classification. IEEE Transactions on Systems, Man and Cybernetics, SMC vol. 3 no. 6, pp. 610-620.

Examples

data<-c(0,0,1,1,0,0,1,1,0,2,2,2,2,2,3,3)
mat<-matrix(data,nrow=4, byrow=TRUE)
GLCM<-genGLCM(2,1,mat)
(GLCM)


## The function is currently defined as
function (direction, distance, rawmat) 
{
    number_coloums <- max(rawmat) + 1
    number_rows <- max(rawmat) + 1
    GLCM <- matrix(0, ncol = 255, nrow = 255)
    (GLCM)
    if (direction == 1) {
        for (i in 1:number_coloums - 1) {
            for (a in 1:number_rows) {
                GLCM[rawmat[a, i] + 1, rawmat[a, i + 1] + 1] <- GLCM[rawmat[a, 
                  i] + 1, rawmat[a, i + 1] + 1] + 1
            }
        }
    }
    if (direction == 2) {
        for (i in 1:number_coloums) {
            for (a in 1:number_rows - 1) {
                GLCM[rawmat[a, i] + 1, rawmat[a + 1, i] + 1] <- GLCM[rawmat[a, 
                  i] + 1, rawmat[a + 1, i] + 1] + 1
            }
        }
    }
    transGLCM <- t(GLCM)
    print("INVERTIERT")
    GLCM <- GLCM + transGLCM
    GLCMprob <- round(GLCM/sum(GLCM), digits = 4)
    return(GLCMprob)
  }