利用opencv逼近二值圖像的邊界點並過濾不需要的邊界達到尋邊效果

1、HYPERLINK /rocky69/article/details/7244226利用opencv逼近二值圖像的邊界點，並過濾不需要的邊界，達到尋邊效果 二值化圖像；利用黑白像素值求差，得到邊緣點；過濾邊緣點找到合適區域；利用cvFitLine2D擬合線。 做的比較粗糙，搜尋時間在10ms左右，希望有研究opencv的朋友斧正。效果預覽：、 cpp HYPERLINK /c2716266/article/details/7191460#view plainHYPERLINK /c2716266/article/details/7191460#copyvoid CvProcess:FindLi

2、ne( IplImage* orgImg ,/原始圖像 IplImage*runImg,/顯示用圖像 CvRect rec,/roi int thredValue,/二值化閾值 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);/原始圖像拷貝到顯示圖像用於顯示 IplImage* thrdImg = cvCreateImage(/創建一個單通道二值圖像用於各種處理 cvSize(orgImg-width,orgImg-height), IPL

3、_DEPTH_8U, 1); /將原始圖像轉換為單通道灰度圖像 cvCvtColor(runImg,thrdImg,CV_BGR2GRAY); /二值化處理 cvThreshold( thrdImg, thrdImg, thredValue, 255, CV_THRESH_BINARY); / cvNamedWindow(); / cvShowImage(,thrdImg); if(rec.width0&rec.width0&rec.widthIMAGE_HEIGHT)/判斷是否有適合的ROI區域 /設置ROI cvSetImageROI(runImg,rec); cvSetImageROI(

4、thrdImg,rec); /搜索邊界 CvPoint2D32f *EdgePoint2D = /用於存儲搜索到的所有邊界點 (CvPoint2D32f *)malloc(IMAGE_HEIGHT*IMAGE_WIDTH) * sizeof(CvPoint2D32f); CvPoint2D32f *RelEdgePoint2D =/用於存儲搜索到的正確的點 (CvPoint2D32f *)malloc(IMAGE_HEIGHT*IMAGE_WIDTH) * sizeof(CvPoint2D32f); int EdgePoint2DCount=0;/點計數 int RelEdgePoint2DC

5、ount=0; /真實點計數 float *line = new float4; /用於畫逼近線 byte ftData=0,secData=0; /搜索邊界點所需資源 /得到ROI區域內的搜索線 std:vector searchlines = GetRecLines(rec,lineAccuracy,SearchDirection); switch(SearchDirection)/搜索方向 case TB : /上到下縱向搜索 for (int i=0;iroi-width;i+) for (int j=0;jroi-height-1;j+) /上下搜索所有的差值大於200的點 ftDa

6、ta=CV_IMAGE_ELEM(thrdImg,uchar,thrdImg-roi-yOffset+j,thrdImg-roi-xOffset+i);/利用宏直接得到結果 /ftData=(thrdImg-imageData + i * thrdImg-widthStep)j;/注意這裡是 寬度用的是 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-f

7、tData200)/黑到白 for(int n=0;nsearchlines.size();n+)/搜索在搜索線上的點 if (searchlinesn.PTS.x=i&searchlinesn.PTS.yj) EdgePoint2DEdgePoint2DCount=cvPoint2D32f(i,j); if (EdgePoint2DCount0)/大於2點時比較 bool realPoint=TRUE; /刪除X坐標相同的縱向點，減少逼近時誤判幾率 for (int m=1;m200)/白到黑 for(int n=0;nsearchlines.size();n+)/搜索在搜索線上的點 if

8、(searchlinesn.PTS.x=i&searchlinesn.PTS.yj) EdgePoint2DEdgePoint2DCount=cvPoint2D32f(i,j); if (EdgePoint2DCount0)/大於2點時比較 bool realPoint=TRUE; /刪除X坐標相同的縱向點，減少逼近時誤判幾率 for (int m=1;m2)/當找到的點大於2時在搜尋逼近線 /找出逼近線 cvFitLine2D(RelEdgePoint2D,RelEdgePoint2DCount, CV_DIST_L1,NULL,0.01,0.01,line); CvPoint FirstP

9、oint;/起點 CvPoint LastPoint;/終點 FirstPoint.x=int (line2-1000*line0); FirstPoint.y=int (line3-1000*line1); LastPoint.x=int (line2+1000*line0); LastPoint.y=int (line3+1000*line1); cvLine( runImg, FirstPoint, LastPoint, CV_RGB(255,0,0), 1, CV_AA);/畫出逼近線 break; case LR : /左到右橫向搜索 for (int j=0;jroi-height

10、;j+) for (int i=0;iroi-width-1;i+) ftData=CV_IMAGE_ELEM(thrdImg,uchar,thrdImg-roi-yOffset+j,thrdImg-roi-xOffset+i);/利用宏直接得到結果 /ftData=(thrdImg-imageData + i * thrdImg-widthStep)j;/注意這裡是 寬度用的是 widthStep 而不是 width secData=CV_IMAGE_ELEM(thrdImg,uchar,thrdImg-roi-yOffset+j,thrdImg-roi-xOffset+i+1); swit

11、ch(EdgePolarity) case B2W: if(secData-ftData200)/黑到白 for(int n=0;nsearchlines.size();n+)/point in searchlines if (searchlinesn.PTS.y=j&searchlinesn.PTS.xi) EdgePoint2DEdgePoint2DCount=cvPoint2D32f(i,j); if (EdgePoint2DCount0)/大於2點時比較 bool realPoint=TRUE; for (int m=1;m200)/白到黑 for(int n=0;nsearchlin

12、es.size();n+)/找出在搜索線上的點 if (searchlinesn.PTS.y=j&searchlinesn.PTS.xi) EdgePoint2DEdgePoint2DCount=cvPoint2D32f(i,j); if (EdgePoint2DCount0)/大於2點時比較 bool realPoint=TRUE; for (int m=1;m2) cvFitLine2D(RelEdgePoint2D,RelEdgePoint2DCount, CV_DIST_L1,NULL,0.01,0.01,line); CvPoint FirstPoint;/起點 CvPoint La

13、stPoint;/終點 FirstPoint.x=int (line2-1000*line0); FirstPoint.y=int (line3-1000*line1); LastPoint.x=int (line2+1000*line0); LastPoint.y=int (line3+1000*line1); cvLine( runImg, FirstPoint, LastPoint, CV_RGB(255,0,0), 1, CV_AA);/畫出逼近線 break; /釋放資源 free(EdgePoint2D); free(RelEdgePoint2D); delete line; se

14、archlines.clear(); cvResetImageROI(runImg); cvResetImageROI(thrdImg); DrawRecLines(runImg,rec,lineAccuracy,SearchDirection); /釋放資源 cvReleaseImage(&thrdImg); /畫ROI時候 連帶畫出搜索線 void CvProcess:DrawRecLines(IplImage* runImg,CvRect rec,int lineAccuracy,int SearchDirection) cvRectangleR(runImg,rec,CV_RGB(0,

15、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;ilineAccuracy;i+) CvPoint Ps=cvPoint(double)rec.width/lineAccuracy)*i+RecPS.x,RecPS.y); CvPoint Pe=cvPoint(double)rec.width/lineAccuracy)*i+RecPS.x,

16、RecPE.y); cvLine(runImg,Ps,Pe,CV_RGB(0,255,255),1, CV_AA,0); break; case LR : for (int i=1;ilineAccuracy;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,

17、0); break; /得到ROI內部搜索線 std:vector CvProcess:GetRecLines(CvRect rec,int lineAccuracy,int SearchDirection) std:vector SearchLines; CLine line; rec.x=0;/坐標轉換值ROI區域 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;ilineAccuracy;i+) line.PTS=cvPoint(double)rec.width/lineAccuracy)*i+RecPS.x,RecPS.y); line.PTE=cvPoint(double)rec.width/lineAccuracy)*i+RecPS.x,RecPE.