using genetic algorithms for image segmentation of the source. Matlab-based platform, in a fit- and two-dimensional segmentation.

segment_ga
..........\2d_ksw_qiongju.asv
..........\2d_ksw_qiongju.m
..........\cross.asv
..........\cross.m
..........\cross1.asv
..........\cross1.m
..........\cross_2d.asv
..........\cross_2d.m
..........\cross_2d1.m
..........\datas
..........\.....\ksw_2d_ga_improve.fig
..........\.....\ksw_2d_ga_qiongju_noise.fig
..........\.....\ksw_ga_improve.fig
..........\.....\ksw_ga_improve_noise.fig
..........\.....\ksw_qiongju.fig
..........\.....\ksw_qiongju_noise.fig
..........\.....\二维最佳直方图熵法及传统遗传算法.txt
..........\.....\二维最佳直方图熵法及改进遗传算法.txt
..........\.....\二维最佳直方图熵法及穷举法.txt
..........\.....\最佳直方图熵法及改进遗传算法.txt
..........\.....\最佳直方图熵法及穷举法.txt
..........\ga_main.asv
..........\ga_main.m
..........\hist2.m
..........\ksw.asv
..........\ksw.m
..........\ksw_2d.asv
..........\ksw_2d.m
..........\ksw_2d_ga.asv
..........\ksw_2d_ga.m
..........\ksw_2d_ga_improve.asv
..........\ksw_2d_ga_improve.m
..........\ksw_2d_qiongju.m
..........\ksw_ga.asv
..........\ksw_ga.m
..........\ksw_ga_improve.asv
..........\ksw_ga_improve.m
..........\ksw_qiongju.asv
..........\ksw_qiongju.m


..........\mutation.m
..........\mutation1.m
..........\mutation_2d.asv
..........\mutation_2d.m
..........\mutation_2d1.m
..........\otosu.asv
..........\otosu.m
..........\rice.tif
..........\rice_noise.tif
..........\rice_noise1.tif
..........\select.asv
..........\select.m
..........\select1.asv
..........\select1.m
..........\select_2d.asv
..........\select_2d.m
..........\select_2d1.asv
..........\select_2d1.m
..........\sourseimage.m
..........\threshold_ksw.asv
..........\threshold_ksw.m
..........\window_function.fig
..........\window_function.m

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