Table 2 GLCM feature for Non-Polished (class 0) and polished (class1) samples.

From: Texture-based image analysis and explainable machine learning for polished asphalt identification in pavement condition monitoring

Class

Sample

ᶿ

Contrast

Correlation

Dissimilarity

Energy

Homogeneity

ASM

0

View full size image

414.39

0.837

13.76

0.014

0.015

0.00022

45°

823.26

0.677

19.72

0.013

0.013

0.000191

90°

504.48

0.802

15.12

0.015

0.015

0.000225

135°

414.39

0.837

13.76

0.014

0.015

0.00022

0

View full size image

209.86

0.828

10.14

0.018

0.114

0.000327

45°

282.56

0.769

11.78

0.016

0.099

0.000286

90°

133.99

0.890

8.09

0.0139

0.139

0.000393

135°

209.86

0.828

10.14

0.018

0.114

0.000327

1

View full size image

414.71

0.862

13.79

0.014

0.104

0.000214

45°

844.87

0.719

19.88

0.012

0.077

0.000158

90°

584.72

0.806

16.22

0.013

0.092

0.000188

135°

414.71

0.862

13.79

0.014

0.104

0.000214

1

View full size image

431.63

0.865

14.47

0.012

0.091

0.000165

45°

1027.82

0.678

22.65

0.010

0.061

0.000115

90°

659.68

0.793

17.86

0.011

0.078

0.00014

135°

431.63

0.865

14.47

0.012

0.091

0.000165