类似下面？

 void ImageBinarization(IplImage *src)  
85.{   /*对灰度图像二值化，自适应门限threshold*/  
86.    int i,j,width,height,step,chanel,threshold;  
87.    /*size是图像尺寸，svg是灰度直方图均值，va是方差*/  
88.    float size,avg,va,maxVa,p,a,s;  
89.    unsigned char *dataSrc;  
90.    float histogram[256];  
91.  
92.    width = src->width;  
93.    height = src->height;  
94.    dataSrc = (unsigned char *)src->imageData;  
95.    step = src->widthStep/sizeof(char);  
96.    chanel = src->nChannels;  
97.    /*计算直方图并归一化histogram*/  
98.    for(i=0; i<256; i++)  
99.        histogram[i] = 0;  
100.    for(i=0; i<height; i++)  
101.        for(j=0; j<width*chanel; j++)  
102.        {  
103.            histogram[dataSrc[i*step+j]-'0'+48]++;  
104.        }  
105.        size = width * height;  
106.        for(i=0; i<256; i++)  
107.            histogram[i] /=size;  
108.        /*计算灰度直方图中值和方差*/  
109.        avg = 0;  
110.        for(i=0; i<256; i++)  
111.            avg += i*histogram[i];  
112.        va = 0;  
113.        for(i=0; i<256; i++)  
114.            va += fabs(i*i*histogram[i]-avg*avg);  
115.        /*利用加权最大方差求门限*/  
116.        threshold = 20;  
117.        maxVa = 0;  
118.        p = a = s = 0;  
119.        for(i=0; i<256; i++)  
120.        {  
121.            p += histogram[i];  
122.            a += i*histogram[i];  
123.            s = (avg*p-a)*(avg*p-a)/p/(1-p);  
124.            if(s > maxVa)  
125.            {  
126.                threshold = i;  
127.                maxVa = s;  
128.            }  
129.        }  
130.        /*二值化*/  
131.        for(i=0; i<height; i++)  
132.            for(j=0; j<width*chanel; j++)  
133.            {  
134.                if(dataSrc[i*step+j] > threshold)  
135.                    dataSrc[i*step+j] = 255;  
136.                else  
137.                    dataSrc[i*step+j] = 0;  
138.            }  
139.}