Comparative Analysis of the Performance of Complex Texture Clustering Driven by Computational Intelligence Methods Using Multiple Clustering Models

Table 1

Comparative analysis for running time.

Images	Size	Cluster	FCM	FSC	GMM	MEC	Kmeans	Mean-shift
T21	100 × 100	2	34.51	6.32	7.50	3.26	3.55	15.93
T22	100 × 100	2	9.11	5.59	8.10	3.42	3.45	28.42
T31	100 × 100	3	21.99	5.64	16.84	4.39	5.94	9.77
T32	100 × 100	3	18.69	7.74	8.29	4.07	4.58	15.45
T41	100 × 100	4	18.69	10.40	58.70	6.87	6.99	11.74
D1	124 × 124	7	22.85	23.34	192.58	17.77	17.16	24.93
Z2	100 × 100	5	34.13	14.24	62.53	13.12	13.30	28.61
Z3	100 × 100	2	23.65	4.34	10.39	3.74	3.44	13.62
Z4	100 × 100	2	13.87	4.21	9.93	3.93	4.06	16.45
Z5	100 × 100	2	7.62	3.25	20.93	2.73	3.42	4.80