Table 3.
Brief overview of various feature extraction methods
| Method | Description |
|---|---|
| First Order Statistics (FOS) | Average gray level (Mean), standard deviation, variance, skewness, kurtosis, uniformity, energy, entropy |
| Statistical feature matrix (SFM) | Coarseness, Contrast, Periodicity, and Roughness |
| Law’s Texture Energy Measures | Law’s texture energy measures based on five coefficient vectors to represent level (L), edge (E), spot (S), ripple (R), and wave (W). In total 18 texture features can be extracted |
| FPS | Radial Sum and Angular Sum of the discrete Fourier transform |
| Fractal | Hurst exponent, fractal dimension |
| Gray-Level Difference Statistics (GLDS) | Contrast, differential mean, difference entropy, inverse difference moment, angular second moment |
| Gray-level Co-occurrence Matrix (GLCM) | Energy, Entropy, Dissimilarity, Contrast, Correlation, Homogeneity, Autocorrelation, Cluster shade, Cluster prominence, Maximum probability, Sum of Squares, Sum Average, Sum Variance, Sum Entropy, Difference Variance, Difference Entropy, Information measure of Correlation, Inverse Difference moment-Normalized |
| Moment Invariant (MI) | A set of moments invariant to rotation, scaling, and translation derived from second and third normalised central moments |
| Gradient based features | Mean, Variance, Kurtosis, Skewness, and percentage of pixels with non-zero gradient |
| Gray-level run-length matrix (GLRLM) | Short run emphasis, Long run emphasis, Gray-lvel non-uniformity, Run-length non-uniformity, Run percentage, Low gray-level run emphasis, High gray-level run emphasis, Short run high gray-level emphasis, Long run low gray-level emphasis, Long run high gray-level emphasis |
| Gabor Wavelet Transform (GWT) | Mean and standard deviation of Gabor output images obtained by using a set of Gabor wavelets at different scales and orientations |
| Geometric | Centre of gravity x, Centre of gravity j, Height, Width, Area, Perimeter, Roundness, Euler number, Major axis length, Minor axis length, Orientation, Solidity, Extent, Eccentricity, Convex area, Danielsson factor, Filled area |
| Frequency-domain | Discrete Cosine Transform (DCT) features, Discrete Wavelet Transform (DWT) features, Wavelet Packet Transform (WPT) features, Curvelet Transform (CT) features, Stationary Wavelet Transform (SWT) |
| Phase congruency | Variance, contrast, covariance |
| Gabor texture | Multiple Gabor filters having different frequencies and orientation can be used to extract specific features from an image |