利用opencv逼近二值图像的边界点，并过滤不需要的边界，达到寻边效果。（转载请说明出处）

void CvProcess::FindLine(
IplImage* orgImg ,//原始图像
IplImage*runImg,//显示用图像
CvRect rec,//roi
int thredValue,//二值化阈值
int lineAccuracy,//搜索精度
int SearchDirection,//搜索方向
int EdgePolarity)//搜索方式 黑到白 白到黑

{
cvCopy(orgImg,runImg);//原始图像拷贝到显示图像用于显示
IplImage* thrdImg = cvCreateImage(//创建一个单通道二值图像用于各种处理
cvSize(orgImg->width,orgImg->height),
IPL_DEPTH_8U,
1);
//将原始图像转换为单通道灰度图像
cvCvtColor(runImg,thrdImg,CV_BGR2GRAY);
//二值化处理
cvThreshold(
thrdImg,
thrdImg,
thredValue,
255,
CV_THRESH_BINARY);

// 	cvNamedWindow("");
// 	cvShowImage("",thrdImg);
if(rec.width>0&&rec.width<IMAGE_WIDTH&&rec.height>0&&rec.width<IMAGE_HEIGHT)//判断是否有适合的ROI区域
{   //设置ROI
cvSetImageROI(runImg,rec);
cvSetImageROI(thrdImg,rec);

//搜索边界
CvPoint2D32f *EdgePoint2D = //用于存储搜索到的所有边界点
(CvPoint2D32f *)malloc((IMAGE_HEIGHT*IMAGE_WIDTH) * sizeof(CvPoint2D32f));
CvPoint2D32f *RelEdgePoint2D =//用于存储搜索到的正确的点
(CvPoint2D32f *)malloc((IMAGE_HEIGHT*IMAGE_WIDTH) * sizeof(CvPoint2D32f));
int EdgePoint2DCount=0;//点计数
int RelEdgePoint2DCount=0;	//真实点计数
float *line = new float[4];	//用于画逼近线
byte ftData=0,secData=0;	//搜索边界点所需资源
//得到ROI区域内的搜索线
std::vector<CLine> searchlines = GetRecLines(rec,lineAccuracy,SearchDirection);
switch(SearchDirection)//搜索方向
{
case TB :
//上到下纵向搜索
for (int i=0;i<thrdImg->roi->width;i++)
{
for (int j=0;j<thrdImg->roi->height-1;j++)
{   //上下搜索所有的差值大于200的点
ftData=CV_IMAGE_ELEM(thrdImg,uchar,thrdImg->roi->yOffset+j,thrdImg->roi->xOffset+i);//利用宏直接得到结果
//ftData=(thrdImg->imageData + i * thrdImg->widthStep)[j];//注意这里是 宽度用的是 widthStep 而不是 width
secData=CV_IMAGE_ELEM(thrdImg,uchar,thrdImg->roi->yOffset+j+1,thrdImg->roi->xOffset+i);
switch(EdgePolarity)
{
case B2W:
if(secData-ftData>200)//黑到白
{
for(int n=0;n<searchlines.size();n++)//搜索在搜索线上的点
{
if (searchlines
.PTS.x==i&&searchlines
.PTS.y<j
&&searchlines
.PTE.y>j)
{
EdgePoint2D[EdgePoint2DCount]=cvPoint2D32f(i,j);
}
}
if (EdgePoint2DCount>0)//大于2点时比较
{
bool realPoint=TRUE;
//删除X坐标相同的纵向点，减少逼近时误判几率
for (int m=1;m<=EdgePoint2DCount;m++)
{
if(EdgePoint2D[EdgePoint2DCount].x == EdgePoint2D[EdgePoint2DCount-m].x)
{
realPoint=FALSE;
}
}
if(realPoint)//得到非重复点并画出
{
RelEdgePoint2D[RelEdgePoint2DCount]=cvPoint2D32f(i,j);
cvCircle(runImg,cvPoint(i,j),
1,CV_RGB(255,0,0),2, CV_AA,0);	//画点
RelEdgePoint2DCount++;
}
}
EdgePoint2DCount++;
}
break;

case W2B:
if(ftData-secData>200)//白到黑
{
for(int n=0;n<searchlines.size();n++)//搜索在搜索线上的点
{
if (searchlines
.PTS.x==i&&searchlines
.PTS.y<j
&&searchlines
.PTE.y>j)
{
EdgePoint2D[EdgePoint2DCount]=cvPoint2D32f(i,j);
}
}
if (EdgePoint2DCount>0)//大于2点时比较
{
bool realPoint=TRUE;
//删除X坐标相同的纵向点，减少逼近时误判几率
for (int m=1;m<=EdgePoint2DCount;m++)
{
if(EdgePoint2D[EdgePoint2DCount].x == EdgePoint2D[EdgePoint2DCount-m].x)
{
realPoint=FALSE;
}
}
if(realPoint)//得到非重复点并画出
{
RelEdgePoint2D[RelEdgePoint2DCount]=cvPoint2D32f(i,j);
cvCircle(runImg,cvPoint(i,j),
1,CV_RGB(255,0,0),2, CV_AA,0);	//画点
RelEdgePoint2DCount++;
}
}
EdgePoint2DCount++;
}
break;
}
}
}
if(RelEdgePoint2DCount>2)//当找到的点大于2时在搜寻逼近线
{	//找出逼近线
cvFitLine2D(RelEdgePoint2D,RelEdgePoint2DCount, CV_DIST_L1,NULL,0.01,0.01,line);
CvPoint FirstPoint;//起点
CvPoint LastPoint;//终点
FirstPoint.x=int (line[2]-1000*line[0]);
FirstPoint.y=int (line[3]-1000*line[1]);
LastPoint.x=int (line[2]+1000*line[0]);
LastPoint.y=int (line[3]+1000*line[1]);
cvLine( runImg, FirstPoint, LastPoint, CV_RGB(255,0,0), 1, CV_AA);//画出逼近线
}
break;

case LR :
//左到右横向搜索
for (int j=0;j<thrdImg->roi->height;j++)
{
for (int i=0;i<thrdImg->roi->width-1;i++)
{
ftData=CV_IMAGE_ELEM(thrdImg,uchar,thrdImg->roi->yOffset+j,thrdImg->roi->xOffset+i);//利用宏直接得到结果
//ftData=(thrdImg->imageData + i * thrdImg->widthStep)[j];//注意这里是 宽度用的是 widthStep 而不是 width
secData=CV_IMAGE_ELEM(thrdImg,uchar,thrdImg->roi->yOffset+j,thrdImg->roi->xOffset+i+1);
switch(EdgePolarity)
{
case B2W:
if(secData-ftData>200)//黑到白
{
for(int n=0;n<searchlines.size();n++)//point in searchlines
{
if (searchlines
.PTS.y==j&&searchlines
.PTS.x<i
&&searchlines
.PTE.x>i)
{
EdgePoint2D[EdgePoint2DCount]=cvPoint2D32f(i,j);
}
}
if (EdgePoint2DCount>0)//大于2点时比较
{
bool realPoint=TRUE;
for (int m=1;m<=EdgePoint2DCount;m++)//删除y坐标相同的横向点
{
if(EdgePoint2D[EdgePoint2DCount].y == EdgePoint2D[EdgePoint2DCount-m].y)
{
realPoint=FALSE;
}
}
if(realPoint)//得到非重复点并画出
{
RelEdgePoint2D[RelEdgePoint2DCount]=cvPoint2D32f(i,j);
cvCircle(runImg,cvPoint(i,j),
1,CV_RGB(255,0,0),2, CV_AA,0);	//画点
RelEdgePoint2DCount++;
}
}
EdgePoint2DCount++;
}
break;

case W2B:
if(ftData-secData>200)//白到黑
{
for(int n=0;n<searchlines.size();n++)//找出在搜索线上的点
{
if (searchlines
.PTS.y==j&&searchlines
.PTS.x<i
&&searchlines
.PTE.x>i)
{
EdgePoint2D[EdgePoint2DCount]=cvPoint2D32f(i,j);
}
}
if (EdgePoint2DCount>0)//大于2点时比较
{
bool realPoint=TRUE;
for (int m=1;m<=EdgePoint2DCount;m++)//删除X坐标相同的纵向点
{
if(EdgePoint2D[EdgePoint2DCount].y == EdgePoint2D[EdgePoint2DCount-m].y)
{
realPoint=FALSE;
}
}
if(realPoint)//得到非重复点并画出
{
RelEdgePoint2D[RelEdgePoint2DCount]=cvPoint2D32f(i,j);
cvCircle(runImg,cvPoint(i,j),
1,CV_RGB(255,0,0),2, CV_AA,0);	//draw points
RelEdgePoint2DCount++;
}
}
EdgePoint2DCount++;
}
break;
}
}
}
//搜索逼近线
if(RelEdgePoint2DCount>2)
{
cvFitLine2D(RelEdgePoint2D,RelEdgePoint2DCount, CV_DIST_L1,NULL,0.01,0.01,line);
CvPoint FirstPoint;//起点
CvPoint LastPoint;//终点
FirstPoint.x=int (line[2]-1000*line[0]);
FirstPoint.y=int (line[3]-1000*line[1]);
LastPoint.x=int (line[2]+1000*line[0]);
LastPoint.y=int (line[3]+1000*line[1]);
cvLine( runImg, FirstPoint, LastPoint, CV_RGB(255,0,0), 1, CV_AA);//画出逼近线
}
break;
}
//释放资源
free(EdgePoint2D);
free(RelEdgePoint2D);
delete[] line;
searchlines.clear();
cvResetImageROI(runImg);
cvResetImageROI(thrdImg);
DrawRecLines(runImg,rec,lineAccuracy,SearchDirection);
}

//释放资源
cvReleaseImage(&thrdImg);
}

//画ROI时候 连带画出搜索线
void CvProcess::DrawRecLines(IplImage* runImg,CvRect rec,int lineAccuracy,int SearchDirection)
{
cvRectangleR(runImg,rec,CV_RGB(0,255,0),1, CV_AA,0);
CvPoint RecPS=cvPoint(rec.x,rec.y),
RecPE=cvPoint(rec.x+rec.width,rec.y+rec.height);
switch(SearchDirection)
{
case TB :
for (int i=1;i<lineAccuracy;i++)
{
CvPoint Ps=cvPoint(((double)rec.width/lineAccuracy)*i+RecPS.x,RecPS.y);
CvPoint Pe=cvPoint(((double)rec.width/lineAccuracy)*i+RecPS.x,RecPE.y);
cvLine(runImg,Ps,Pe,CV_RGB(0,255,255),1, CV_AA,0);
}
break;
case LR :
for (int i=1;i<lineAccuracy;i++)
{
CvPoint Ps=cvPoint(RecPS.x,((double)rec.height/lineAccuracy)*i+RecPS.y);
CvPoint Pe=cvPoint(RecPE.x,((double)rec.height/lineAccuracy)*i+RecPS.y);
cvLine(runImg,Ps,Pe,CV_RGB(0,255,255),1, CV_AA,0);
}
break;
}

}

//得到ROI内部搜索线
std::vector<CLine> CvProcess::GetRecLines(CvRect rec,int lineAccuracy,int SearchDirection)
{
std::vector<CLine> SearchLines;
CLine line;
rec.x=0;//坐标转换值ROI区域
rec.y=0;
CvPoint RecPS=cvPoint(rec.x,rec.y),
RecPE=cvPoint(rec.x+rec.width,rec.y+rec.height);
switch(SearchDirection)
{
case TB :
for (int i=1;i<lineAccuracy;i++)
{
line.PTS=cvPoint(((double)rec.width/lineAccuracy)*i+RecPS.x,RecPS.y);
line.PTE=cvPoint(((double)rec.width/lineAccuracy)*i+RecPS.x,RecPE.y);
SearchLines.push_back(line);
}
break;
case LR :
for (int i=1;i<lineAccuracy;i++)
{
line.PTS=cvPoint(RecPS.x,((double)rec.height/lineAccuracy)*i+RecPS.y);
line.PTE=cvPoint(RecPE.x,((double)rec.height/lineAccuracy)*i+RecPS.y);
SearchLines.push_back(line);
}
break;
}

return SearchLines;