Table 15.

Comparison results of proposed method with other method for CBIR.

Dataset	Method	mAP	Training rate%, Test rate%	Dimension of proposed method
Corel-1000	CCM + DBPSP [63]	76.10	90, 10	1 × 21
	Block Truncation Coding [57]	77.90	–	1 × 96
	HOG + SURF [64]	80.61	70, 30	–
	Dense SIFT [65]	84.20	50, 50	1 × 128
	SURF + FREAK [66]	86	70, 30	1 × 128
	SURF + MSER [67]	88	70, 30	1 × 128
	Fusion features [55]	83.50	–	–
	AlexNet CNN [44]	93.80	–	1 × 4096
	Proposed method	95.80	3-fold cross validation	1 × 128
OT	Co-occurance matrix [43]	76.39	10-fold cross validation	1 × 9
	Color moment + Angular Radial Transform + Edge histogram [58]	50.59	85, 15	–
	Relevance Feedback [59]	79	–	–
	Proposed method	93.91	3-fold cross validation	1 × 128
FP	Co-occurance matrix [43]	78.83	10-fold cross validation	1 × 9
	Proposed method	86.86	3-fold cross validation	1 × 128