求opencv用C++实现边缘检测以及求两直线之间的距离

int main()
{
IplImage* src;
src=cvLoadImage("D:\\image\\line.jpg");
{
IplImage* dst = cvCreateImage( cvGetSize(src), 8, 1 );
IplImage* color_dst = cvCreateImage( cvGetSize(src), 8, 3 );
CvMemStorage* storage = cvCreateMemStorage(0);//存储检测到线段，当然可以是N*1的矩阵数列，如果实际的直线数量多余N，那么最大可能数目的线段被返回
CvSeq* lines = 0;
int i;
IplImage* src1=cvCreateImage(cvSize(src->width,src->height),IPL_DEPTH_8U,1);

cvCvtColor(src, src1, CV_BGR2GRAY);  //把src转换成灰度图像保存在src1中，注意进行边缘检测一定要换成灰度图
cvCanny( src1, dst, 50, 200, 3 );//参数50，200的灰度变换

cvCvtColor( dst, color_dst, CV_GRAY2BGR );

lines = cvHoughLines2( dst, storage, CV_HOUGH_PROBABILISTIC, 1, CV_PI/180, 80, 30, 10 );
for( i = 0; i < lines->total; i++ )
{
CvPoint* line = (CvPoint*)cvGetSeqElem(lines,i);
cvLine( color_dst, line[0], line[1], CV_RGB(255,255,0), 3, 8 );
double k=(double)(line[1].y-line[0].y)/(double)(line[1].x-line[0].x);
double d=line[0].y-line[0].x*k;
printf("This is the %d line, this line is y = %.2f x + %.2f \n",i+1,k,d);
}

cvNamedWindow( "Source", 1 );
cvShowImage( "Source", src );

cvNamedWindow( "Hough", 1 );
cvShowImage( "Hough", color_dst );

cvWaitKey(0);
}
}