Fast and Automatic Fuzzy C-Means Clustering Color Image Segmentation Algorithm

Fig. 3. Color space, histogram, and number of clusters of images. (a) Original images; (b) original image color space;(c) superpixel image color space; (d) original image histogram; (e) superpixel image histogram; (f) number of clusters

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Fig. 4. Segmentation results of 5 algorithms on BSDS500 database. (a) Original images; (b) FCM; (c) SFFCM; (d) FCM_SICM;(e) AFCF; (f) proposed method

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Fig. 5. Segmentation results of proposed algorithm on AID and MSRC databases. (a) Original images; (b) superpixel segmentation;(c) segmentation results of proposed algorithm

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Table 1. Five algorithms for average segmentation index of color images
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Table 1. Five algorithms for average segmentation index of color images
Segmentation index $S A / %$ $V_{P C} / %$ $V_{P E} / %$ Running time /s
FCM 92.78 92.65 23.27 17
FCM_SICM 90.25 91.89 25.52 22
SFFCM 89.88 90.13 19.89 16
AFCF 89.90 91.92 17.72 28
Proposed method 93.92 92.80 13.43 20

Table 2. 5 algorithm time complexity

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Table 2. 5 algorithm time complexity

Algorithm	Calculation step $E$	Calculation step function $E (n)$	Time complexity
FCM	$H \times W \times K \times T$	$n^{4}$	$O (n^{4})$
FCM_SICM	$H \times W \times K \times T$	$n^{4}$	$O (n^{4})$
SFFCM	$H \times W \times h^{2} \times T_{M} + T_{W} \times N \times K \times T$	$n^{5} + n^{4}$	$O (n^{5})$
AFCF	$N \times K \times T$	$n^{3}$	$O (n^{3})$
Proposed method	$N \times K \times T$	$n^{3}$	$O (n^{3})$

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Chao Wang, Yongshun Wang, Fan Di. Fast and Automatic Fuzzy C-Means Clustering Color Image Segmentation Algorithm[J]. Laser & Optoelectronics Progress, 2022, 59(22): 2210001

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