Table 7.

Details of the 36 features resulting by the forward selection method using Näive Bayes Classifier.

36 features Forward selection	Haralick features			Haar-like features	Statistical features
	Orientation	Coordinate	Mask size	Type	Mask size	Entry
Contrast*	135	Y	3
Gradient*					5	$\overline{EC}$
Correlation	135	X	3
Position*						Coordinates
Normalized gray level*						Value
Correlation*	45	X	5
Gradient*					5	$\overline{DF}$
Correlation*	90	Y	9
Correlation	45	Y	7
Skewness*					7
Homogeneity*	90	X	9
Correlation	0	Y	5
Correlation	90	Z	5
Correlation*	45	X	3
Correlation	135	Z	9
Correlation	90	Y	5
Correlation	135	Z	5
Correlation	0	Z	7
Correlation	90	Z	7
Correlation	90	Z	9
Correlation	0	Y	3
Correlation	135	X	3
Correlation	0	Z	9
Template*				1
Skewness*					5
Correlation	90	Z	3
Correlation	45	X	5
Gradient					3	$\overline{MN}$
Template				2
Correlation*	45	X	9
Correlation	45	Y	5
Correlation	90	Y	7
Correlation	45	Z	5
Gradient					9	$\overline{DF}$
Homogeneity	0	Z	9
Correlation	0	Y	9

The asterisk indicates the entries also present in the list of 23 SBE features. For Haralick features, the orientation in degrees, reference coordinate, and the size of the cubic mask used are reported. In case of Haar-like features, the entry value indicates the template type used (see Figure 2). For statistical/positional kind the size of the cubic mask used or the self-explained value is lister, depending on the specific feature type. In particular for gradients, the column named Entry indicates the segment of the reference diagonal as shown in Figure 3. All the features are listed in top-down order of their inclusion during the SFS procedure execution.