R: Generalized Application of Co-Occurrence Matrices and Haralick Texture

# Generalized Application of Co-Occurrence Matrices and Haralick Texture

## Documentation for package ‘gtexture’ version 1.0.1

- DESCRIPTION file
- Package NEWS

## Help Pages

autocorrelation | Autocorrelation Metric for a GLCM or GLCM equivalent matrix
autocorrelation.default | Autocorrelation Metric for a GLCM or GLCM equivalent matrix
autocorrelation.FitLandDF | Autocorrelation Metric for a GLCM or GLCM equivalent matrix
autocorrelation.matrix | Autocorrelation Metric for a GLCM or GLCM equivalent matrix
cluster_prom | Cluster Prominence Metric for a GLCM
cluster_prom.default | Cluster Prominence Metric for a GLCM
cluster_prom.FitLandDF | Cluster Prominence Metric for a GLCM
cluster_prom.matrix | Cluster Prominence Metric for a GLCM
cluster_shade | Cluster Shade Metric for a GLCM
cluster_shade.default | Cluster Shade Metric for a GLCM
cluster_shade.FitLandDF | Cluster Shade Metric for a GLCM
cluster_shade.matrix | Cluster Shade Metric for a GLCM
comat | Calculate Co-Occurrence Matrix
compute_all_metrics | Convenience function to compute all haralick texture features
contrast | Contrast Metric for a GLCM
contrast.default | Contrast Metric for a GLCM
contrast.FitLandDF | Contrast Metric for a GLCM
contrast.matrix | Contrast Metric for a GLCM
correlation | Correlation Metric for a GLCM
correlation.default | Correlation Metric for a GLCM
correlation.FitLandDF | Correlation Metric for a GLCM
correlation.matrix | Correlation Metric for a GLCM
differenceEntropy.matrix | Difference entropy is the entropy of marginal distribution of the difference in gray-level value equivalents x-y
discretize | Discretize Numeric Variable Into Categories
discretize.FitLandDF | Discretize Numeric Variable Into Categories
discretize.integer | Discretize Numeric Variable Into Categories
discretize.list | Discretize Numeric Variable Into Categories
discretize.numeric | Discretize Numeric Variable Into Categories
dissimilarity.matrix | Dissimilarity of a co-occurrence matrix
energy | Energy Metric for a GLCM
energy.default | Energy Metric for a GLCM
energy.FitLandDF | Energy Metric for a GLCM
energy.matrix | Energy Metric for a GLCM
entropy | Entropy Metric for a GLCM
entropy.default | Entropy Metric for a GLCM
entropy.FitLandDF | Entropy Metric for a GLCM
entropy.matrix | Entropy Metric for a GLCM
equal_discrete | Function Factory for Even Discretization Functions
euclidean | Euclidean Distance Function Factory
get_comatrix | Calculate Co-Occurrence Matrix
get_comatrix.default | Calculate Co-Occurrence Matrix
get_comatrix.FitLandDF | Calculate Co-Occurrence Matrix
get_comatrix.igraph | Calculate Co-Occurrence Matrix
glcm_marginals | Marginal distributions of the GLCM
glcm_mean | Statistics of GLCM
glcm_statistics | Statistics of GLCM
glcm_variance | Statistics of GLCM
homogeneity | Homogeneity Metric for a GLCM
homogeneity.default | Homogeneity Metric for a GLCM
homogeneity.FitLandDF | Homogeneity Metric for a GLCM
homogeneity.matrix | Homogeneity Metric for a GLCM
inv_diff | Inverse Difference Metric for a GLCM
inv_diff.default | Inverse Difference Metric for a GLCM
inv_diff.FitLandDF | Inverse Difference Metric for a GLCM
inv_diff.matrix | Inverse Difference Metric for a GLCM
kmeans_discrete | Kmeans clustering discretization
manhattan | Manhattan Distance Function Factory
max_prob | Maximum Probability Metric for a GLCM
max_prob.default | Maximum Probability Metric for a GLCM
max_prob.FitLandDF | Maximum Probability Metric for a GLCM
max_prob.matrix | Maximum Probability Metric for a GLCM
mu_x.matrix | Statistics of GLCM
mu_y.matrix | Statistics of GLCM
normalize_glcm | Normalize a GLCM
quantile_discrete | Function to discretize based on quantiles
sum_squares | Sum of Squares Metric for a GLCM
sum_squares.default | Sum of Squares Metric for a GLCM
sum_squares.FitLandDF | Sum of Squares Metric for a GLCM
sum_squares.matrix | Sum of Squares Metric for a GLCM
xminusy_k | Marginal distributions of the GLCM
xplusy_k | Marginal distributions of the GLCM