GASA

  基于遗传模拟退火和Otsu法的图像分割。采用一种基于模拟退火算法(SA)的混合遗传算法(GASA),来进行Otsu方法选择阈值，其中进行求解时是非线性的遗传算法（GA）的应用优化了求阈值过程，并尽可能地减少其运算量,而加入SA则避免了遗传算法(GA)常见的早熟收敛现象,从而实现有效简单的图像分割。 (adopt hybrid genetic algorithm(GASA) based on simulated annealing algorithm,choose threshold by Ostu method,which applicated the non-linear genetic algorithm(GA) allows us to optimize the process of threshold. And, where possible, to reduce the computation. in order to achieve effectivly and simply image segmentation. Combination SA is to avoid the common phenomenon about premature convergence in genetic algorithm (GA) to achieve a simple and effective image segmentation.)

GASA
....\CDIB.CPP
....\CDIB.H
....\DIBPrcs.cpp
....\GASA.APS
....\GASA.clw
....\GASA.cpp
....\GASA.dsp
....\GASA.dsw
....\GASA.h
....\GASA.ncb
....\GASA.opt
....\GASA.plg
....\GASA.rc
....\GASAApi.cpp
....\GASADlg.cpp
....\GASADlg.h
....\GlobalApi.h
....\Hist.cpp
....\Hist.h
....\ReadMe.txt
....\res

....\...\GASA.rc2
....\Resource.h
....\StdAfx.cpp
....\StdAfx.h