An efficient similarity measure for content based image retrieval using memetic algorithm

Figures & data

Fig. 1 The proposed method block diagram.

Fig. 2 Chromosome form.

Fig. 3 Crossover operation.

Fig. 4 Mutation operation.

Fig. 5 A generic pseudo code of the GDA [38].

Table 1 Shows the parameters setting of the MA.

Parameter	Value
GA generation number	1000
Crossover rate	0.90
Mutation rate	0.02
Fitness value for chromosome	0.005
GDA generation number	600
Initial water level	0
Final water level	100

Fig. 6 The pseudo code of the MA [39].

Fig. 7 Similarity measure based on Memetic algorithm for the proposed CBIR technique.

Fig. 8 Shape features extraction steps

Fig. 9 a. QI b. Some retrieved images.

Fig. 10 a. QI b. Some retrieved images.

Fig. 11 a. QI b. Some retrieved images.

Table 2 Recall-Precision measurements.

Groups	Precision	Recall
Buses	0.95	0.74
Mountains	0.82	0.74
Beach	0.893	0.81
Elephants	0.82	0.55
Food	0.88	0.61
Flowers	0.95	0.65
Africa	0.83	0.71
Horses	0.955	0.85
Dinosaurs	0.99	0.741
Buildings	0.74	0.601

Fig. 12 Recall and Precision graph.

Table 3 Comparison results of the proposed method against other retrieval standard methods based on average precision.

Class	Proposed method	[13]	[9]	[33]	[34]	[35]	[36]	[37]
Buses	0.95	0.846	0.95	0.89	0.92	0.88	0.74	0.87
Mountains	0.82	0.811	0.75	0.51	0.74	0.52	0.29	0.53
Beach	0.893	0.892	0.70	0.53	0.64	0.54	0.39	0.56
Elephants	0.82	0.727	0.80	0.57	0.78	0.65	0.30	0.67
Food	0.88	0.871	0.75	0.69	0.81	0.73	0.36	0.74
Flowers	0.95	0.917	0.95	0.89	0.95	0.89	0.85	0.91
Africa	0.83	0.828	0.65	0.56	0.64	0.68	0.45	0.70
Horses	0.955	0.951	0.90	0.78	0.95	0.80	0.56	0.83
Dinosaurs	0.99	0.828	1.00	0.98	0.99	0.99	0.91	0.97
Buildings	0.74	0.632	0.75	0.61	0.70	0.54	0.37	0.57
Average	0.882	0.830	0.820	0.701	0.812	0.722	0.522	0.735

Table 4 Comparison results of the proposed method against other retrieval standard methods based on average recall.

Class	Proposed method	[13]	[9]	[34]	[35]	[36]	[37]
Buses	0.74	0.733	0.19	0.18	0.12	0.09	0.11
Mountains	0.74	0.732	0.15	0.15	0.21	0.13	0.22
Beach	0.81	0.805	0.14	0.13	0.19	0.12	0.19
Elephants	0.55	0.533	0.16	0.16	0.14	0.13	0.15
Food	0.61	0.600	0.15	0.16	0.13	0.12	0.13
Flowers	0.65	0.647	0.19	0.19	0.11	0.08	0.11
Africa	0.71	0.706	0.13	0.13	0.14	0.11	0.15
Horses	0.85	0.848	0.18	0.19	0.13	0.10	0.13
Dinosaurs	0.741	0.726	0.20	0.20	0.10	0.07	0.09
Buildings	0.601	0.585	0.15	0.14	0.17	0.12	0.18
Average	0.7002	0.691	0.164	0.163	0.144	0.107	0.146

Fig. 13 Comparison results of the proposed method against other retrieval standard methods based on precision.

Fig. 14 Comparison results of the proposed method against other retrieval standard methods based on recall.

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