在OpenCV中自适应确定canny算法的分割阈值

时间：2010-10-25 来源：echobs

我在OpenCv原码库中增加了一个函数，用于确定高低阈值。 // 仿照matlab，自适应求高低两个门限
CV_IMPL void AdaptiveFindThreshold(CvMat *dx, CvMat *dy, double *low, double *high)
{
CvSize size;
IplImage *imge=0;
int i,j; CvHistogram *hist;
int hist_size = 255;
    float range_0[]={0,256};
    float* ranges[] = { range_0 };
double PercentOfPixelsNotEdges = 0.7; size = cvGetSize(dx);
imge = cvCreateImage(size, IPL_DEPTH_32F, 1);
// 计算边缘的强度, 并存于图像中
float maxv = 0;
for(i = 0; i < size.height; i++ )
{
   const short* _dx = (short*)(dx->data.ptr + dx->step*i);
        const short* _dy = (short*)(dy->data.ptr + dy->step*i);
   float* _image = (float *)(imge->imageData + imge->widthStep*i);
   for(j = 0; j < size.width; j++)
   {
    _image[j] = (float)(abs(_dx[j]) + abs(_dy[j]));
    maxv = maxv < _image[j] ? _image[j]: maxv;
   }
} // 计算直方图
range_0[1] = maxv;
hist_size = (int)(hist_size > maxv ? maxv:hist_size);
hist = cvCreateHist(1, &hist_size, CV_HIST_ARRAY, ranges, 1);
cvCalcHist( &imge, hist, 0, NULL );
int total = (int)(size.height * size.width * PercentOfPixelsNotEdges);
float sum=0;
int icount = hist->mat.dim[0].size;

float *h = (float*)cvPtr1D( hist->bins, 0 );
for(i = 0; i < icount; i++)
{
   sum += h[i];
   if( sum > total )
    break;
} // 计算高低门限
*high = (i+1) * maxv / hist_size ;
*low = *high * 0.4;
cvReleaseImage( &imge );
cvReleaseHist(&hist);
}
在把cvCanny函数进行以下修改。在函数体中，当程序用两个sobel算子计算完水平和垂直两个方向的梯度强度过后加入以下代码 // 自适应确定阈值
if(low_thresh == -1 && high_thresh == -1)
{
   AdaptiveFindThreshold(dx, dy, &low_thresh, &high_thresh);
}
这样，在调用cvCanny函数时，指定高低门限为－1，则cvCanny函数就自适应确定门限。
最后，别忘

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