Characterization of Complex Image Spatial Structures Based on Symmetrical Weibull Distribution Model for Texture Pattern Classification

Table 4

Classification accuracies of comparative methods. Results marked with asterisk are directly taken from the literature with references and N/A means the corresponding index is absent in the referred literature.

Methods	data sets
	GLCM	89.21 ± 4.52	86.45 ± 5.34	91.45 ± 2.34	90.78 ± 5.34	84.45 ± 1.46
GWT	90.12 ± 3.45	89.12 ± 3.45	92.12 ± 1.45	91.32 ± 2.69	86.12 ± 4.89
MRMRF+PLS-DA	92.87 ± 4.36	89.87 ± 6.36	92.87 ± 3.36	89.87 ± 6.36	85.87 ± 4.36
MRMRF+NLC	91.45 ± 5.23	90.45 ± 1.23	91.85 ± 4.23	90.47 ± 3.82	84.45 ± 5.23
VZ algorithm	95.34 ± 4.54	91.45 ± 2.01	97.12 ± 3.78	(96.40 ± N/A) [28]	90.34 ± 2.14
PATCH	96.12 ± 3.45	(91.80 ± 0.98) [3]	96.80 ± 0.79	(96.19 ± N/A)[28]	91.04 ± 2.02
PATCH-MRF	96.12 ± 3.43	92.04 ± 1.68	97.12 ± 1.34	(97.47 ± N/A)[28]	92.89 ± 1.89
WLD	(97.5 ± 0.6) [12]	94.56 ± 0.83	98.92 ± 1.20	96.98 ± 2.12	93.45 ± 0.89
PRICoLBP+SVM	(96.9 ± N/A)[16]	93.28 ± 0.89	98.68 ± 0.98	98.42 ± 1.78	92.34 ± 1.23
PRICoLBP+PLS-DA	97.62 ± 2.29	93.89 ± 1.02	98.01 ± 1.25	97.89 ± 0.89	93.12 ± 1.56
ISM-TPI (Com3)	98.70 ± 0.89	94.70 ± 1.39	98.82 ± 0.79	98.04 ± 1.89	94.01 ± 0.89