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Classification accuracy of automatic classification system.
| Feature | Method | Performance on the testing set | |
|---|---|---|---|
| Sensitivity | Specificity | ||
| Global geometrical features | PCA + SVM | 4/16 = 25% | 39/48 = 81.3% |
| Global texture features | PCA + SVM | 6/16 = 37.5% | 42/48 = 87.5% |
| Fusion of local features | AdaBoost | 11/16 = 68.8% | 42/48 = 87.5% |
SVM, support vector machine.
PCA, principal component analysis.
