Table 3.
Results of SVM using GLCM features.
SVM using GLCM features | Precision | Recall | F1-score |
---|---|---|---|
Clean | 0.48 | 0.16 | 0.24 |
Dirty | 0.62 | 0.58 | 0.60 |
Thin | 0.77 | 0.94 | 0.84 |
Thick | 0.61 | 0.91 | 0.73 |
Macro avg. | 0.62 | 0.65 | 0.60 |
Weighted avg. | 0.62 | 0.65 | 0.61 |
Average accuracy | 0.651 |