三个经典的图像二值化算法（二）

    kittler 最小分类错误(minimum error thresholding)全局二值化算法，文献出处：J. Kittler and J. Illingworth. Minimum Error Thresholding. Pattern Recognition. 1986. 19(1):41-47。

    效果图如下：

 

 

kittler的c语言程序如下：

 

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void kittlerMet(BYTE **ir, BYTE **ir1,int xz,int yz,int hg,int wt )    

{
    double MAXD = 100000,counts,meanT = 0,w0,miuK,n,miu1,miu2,

    double var1=0,var2=0,minj=100000,index=0;

    int in=0;
    double *imhist;double *Grade;
    imhist= new double[256];
    Grade= new double[256];
    for(int l=0;l<256;l++)
    {
        imhist[l]=0;
        Grade[l]=0.0;
    }
    for(int i=xz;i<xz+hg;i++)

    {
        for(int j=yz;j<yz+wt;j++)
        {
            imhist[ir[i][j]]=imhist[ir[i][j]]+1;
        }

    }
    counts=hg*wt;
    for(l=0;l<256;l++)
    {
        Grade[l]=(double)imhist[l]/counts;
    }
    for(l=0;l<256;l++)
    {
        meanT=meanT+Grade[l]*l;
    }
    w0 = Grade[0];
    miuK = 0;
    imhist[0]=MAXD;
    n = 255;
    for(l=0;l<n;l++)
    {
        w0=w0+Grade[l+1];
        miuK = miuK + (l+1)* Grade[l+1];
        if((w0 < 2.2204*pow(10,-16)) || (w0 > 1-2.2204*pow(10,-16)))
        {
            imhist[l+1]=MAXD;
        }
        else
        {
            miu1 = miuK / w0;
            miu2 = (meanT-miuK) / (1-w0);
            var1=0;var2=0;
            for(i=0;i<=l;i++)
            {
                var1=var1+(pow((i-miu1),2))*Grade[i];
            }
            var1 = var1 / w0;
            for(i=l+1;i<=n;i++)
            {
                var2=var2+(pow((i-miu2),2))*Grade[i];
            }
            var2 = var2 / (1-w0);
            if(var1 > 2.2204*pow(10,-16) && var2 > 2.2204*pow(10,-16) )
                imhist[l+1] = 1+w0*log(var1)+(1-w0)*log(var2)-2*w0*log(w0)-2*(1-w0)*log(1-w0);
            else
                imhist[l+1] = MAXD;
        }
    }
    for(l=0;l<=n;l++)
    {
        if(minj>imhist[l])
            minj=imhist[l];
    }
    for(l=0;l<=n;l++)
    {
        if(minj==imhist[l])
        {
            index=index+l;
            in++;
        }
    }
    index=index/in;
    index=(index-0.999)/n;
  
    for(i=xz;i<xz+hg;i++)

    {
        for(int j=yz;j<yz+wt;j++)
        {
            if(ir[i][j]>=255*index)
                ir1[i][j]=1;
            else
                ir1[i][j]=0;
         }

    }

    delete[] imhist;
    imhist= NULL ;   
    delete[] Grade;
    Grade= NULL;
}