Table 1 Summary Handcrafted Descriptors.... | Emerald Publishing

Table 1

Summary Handcrafted Descriptors.

Name	Parameters	Source	Section
LTP	Multiscale Uniform LTP with two (R,P) configurations: (1, 8) and (2, 16), threshold = 3.	[33]	3.1
MLPQ	Ensemble of LPQ descriptors obtained by varying the filter sizes, the scalar frequency, and the correlation coefficient between adjacent pixel values.	[34]	3.2
CLBP	Completed LBP with two (R,P) configurations: (1,8) and (2,16).	[35]	3.3
RIC	Multiscale Rotation Invariant Co-occurrence of Adjacent LBP with R ∈ {1, 2, 4}.	[36]	3.4
FBSIF	Extension of the BIF by varying the parameters of filter size (SIZE_BSIF, size ∈ {3, 5, 7, 9, 11}) and the threshold for binarizing (FULL_BSIF, th ∈ {−9, −6, −3, 0, 3, 6, 9}).	[37]	3.5
AHP	Adaptive Hybrid Pattern with quantization level = 5 and 2; the (R,P) configurations are (1, 8) and (2, 16).	[38]	3.6
GOLD	Ensemble of Gaussians of LOcal Descriptors extracted using the spatial pyramid decomposition.	[39]	3.7
HOG	Histogram of Oriented Gradients with 30 cells (5 by 6).	[40]	3.8
MOR	A set of MORphological features.	[41]	3.9
CLM	CodebookLess Model. We use the ensemble named CLoVo_3 in [15] based on e-SFT, PCA for dimensionality reduction, and one-vs-all SVM for the training phase.	[42]	3.10
LET	Same parameters used in the source code of [43]	[43]	3.11

Name	Parameters	Source	Section
LTP	Multiscale Uniform LTP with two (R,P) configurations: (1, 8) and (2, 16), threshold = 3.	[33]	3.1
MLPQ	Ensemble of LPQ descriptors obtained by varying the filter sizes, the scalar frequency, and the correlation coefficient between adjacent pixel values.	[34]	3.2
CLBP	Completed LBP with two (R,P) configurations: (1,8) and (2,16).	[35]	3.3
RIC	Multiscale Rotation Invariant Co-occurrence of Adjacent LBP with R ∈ {1, 2, 4}.	[36]	3.4
FBSIF	Extension of the BIF by varying the parameters of filter size (SIZE_BSIF, size ∈ {3, 5, 7, 9, 11}) and the threshold for binarizing (FULL_BSIF, th ∈ {−9, −6, −3, 0, 3, 6, 9}).	[37]	3.5
AHP	Adaptive Hybrid Pattern with quantization level = 5 and 2; the (R,P) configurations are (1, 8) and (2, 16).	[38]	3.6
GOLD	Ensemble of Gaussians of LOcal Descriptors extracted using the spatial pyramid decomposition.	[39]	3.7
HOG	Histogram of Oriented Gradients with 30 cells (5 by 6).	[40]	3.8
MOR	A set of MORphological features.	[41]	3.9
CLM	CodebookLess Model. We use the ensemble named CLoVo_3 in [15] based on e-SFT, PCA for dimensionality reduction, and one-vs-all SVM for the training phase.	[42]	3.10
LET	Same parameters used in the source code of [43]	[43]	3.11