Table 1 Summary of textural features used in the feature model
Feature class | Feature |
|---|---|
First-order statistical features | Mean, Standard deviation |
| Â | Skewness |
| Â | Kurtosis |
Second-order statistical | Energy, Contrast |
features (Haralick) | Correlation, Variance |
| Â | Inverse difference moment |
| Â | Sum average, Sum variance |
| Â | Sum entropy, Entropy |
| Â | Difference variance |
| Â | Difference entropy |
| Â | Information measure of correlation |
| Â | Homogeneity, Autocorrelation |
| Â | Dissimilarity, Cluster shade |
| Â | Cluster prominence |
| Â | Maximum probability |
Gabor filters | 3 scales and 4 orientations |
Kirsch filters | 8 directions |