Infrared and Laser Engineering, Volume. 31, Issue 6, 478(2002)
Approach of FCM clustering image segmentation based on improved evolution strategies
[1] [1] Nikhil R Pal, et al. A review on image segmentation techniques[J]. Patt Recog, 1993, 26(9):1277-1294.
[2] [2] Kim T, Bezbek J C. Optimal tests for the fixed points of the fuzzy C-means algorithms[J]. Patt Recog, 1988, 31:651-663.
[3] [3] Michalewicz Z. Genetic Algorithm+Data Structure=Evolution Programs[M]. New York: Springer, 1992.
[4] [4] David B F. An introduction on simulated evolution optimization[J]. IEEE Trans Neural Networks, 1994, 59(1):3-14.
[5] [5] Bhandarkar S M, Zhang H, et al. Image segmentation using evolutionary computation[J]. IEEE Trans Evolutionary Computation, 1999, 3(1):1-21.
[7] [7] Hall L O, Ozyurt I B. Clustering with a genetically optimized approach[J]. IEEE Trans Evolutionary Computation, 1999, 3(2):103-112.
[8] [8] Held K, Kops E R, et al. Markov random field segmentation of brain MR images[J]. IEEE Trans Medical Imaging, 1997, 16(6):878-886.
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[in Chinese], [in Chinese]. Approach of FCM clustering image segmentation based on improved evolution strategies[J]. Infrared and Laser Engineering, 2002, 31(6): 478