您现在的位置是：首页 > 文章详情

选择轮廓(select_shape)

日期：2015-07-15点击：652收藏

选择轮廓(select_shape)

Halcon是一款运用广泛的图像识别和处理软件。在肤浅的接触中，它的轮廓选择算子(select_shape)给予我很深的印象。结果是往往几行代码就能够产生很好的效果：

比如要得到这样的结果

只需要

 read_image (Image1, 'F:/未来项目/钢管识别/FindTube/FindTube/1.jpg') 
rgb1_to_gray (Image1, GrayImage) 
threshold (GrayImage, Regions, 43, 111) 
connection (Regions, ConnectedRegions) 
select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 150, 666) 
select_shape (SelectedRegions, SelectedRegions1, 'circularity', 'and', 0. 45, 1) 

当然Halcon是在背后做了许多工作的。

几行代码中，比较重要的是算子就是"select_shape"。这个算子的参数很多，我也就比较熟悉这两种。

如果我想在Opencv中也要这样的结果，就需要自己动手尝试实现。实现过程中我采用了类似的函数名表示敬意。

 // selectshape.cpp : 选择轮廓 
 // by: jsxyhelu(1755311380) 
# include  "stdafx.h" 
# include  <iostream > 
# include  "opencv2/core/core.hpp" 
# include  "opencv2/highgui/highgui.hpp" 
# include  "opencv2/imgproc/imgproc.hpp" 
 using  namespace std; 
 using  namespace cv; 
# define  VP  vector <Point >   //用VP符号代替 vector<point> 
RNG  rng( 12345    ); 
 //带有上下限的threshold 
 void threshold2(Mat gray,Mat & thresh, int minvalue, int maxvalue) 
{ 
    Mat thresh1; 
    Mat thresh2; 
    threshold(gray,thresh1, 43, 255, THRESH_BINARY); 
    threshold(gray,thresh2, 111, 255,THRESH_BINARY_INV); 
    thresh  = thresh1  & thresh2; 
} 
 //寻找并绘制出联通区域 
vector <VP > connection2(Mat src,Mat & draw) 
{     
    draw  = Mat : :zeros(src.rows,src.cols,CV_8UC3); 
    vector <VP >contours;     
    findContours(src,contours,CV_RETR_LIST,CV_CHAIN_APPROX_SIMPLE); 
     for ( int i = 0;i <contours.size();i ++) 
    { 
        Scalar  color   = Scalar(rng.uniform( 0, 255),rng.uniform( 0, 255),rng.uniform( 0, 255)); 
        drawContours(draw,contours,i,color, - 1); 
    } 
     return contours; 
} 
 //select_shape 
vector <VP >  selectShapeArea(Mat src,Mat & draw,vector <VP > contours, int minvalue, int maxvalue) 
{ 
    vector <VP > result_contours; 
    draw  = Mat : :zeros(src.rows,src.cols,CV_8UC3); 
     for ( int i = 0;i <contours.size();i ++) 
    {  
         int countour_area  = contourArea(contours[i]); 
         if (countour_area  >minvalue  && countour_area <maxvalue) 
        { 
            result_contours.push_back(contours[i]); 
        } 
    } 
     for ( int i = 0;i <result_contours.size();i ++) 
    { 
        Scalar  color   = Scalar(rng.uniform( 0, 255),rng.uniform( 0, 255),rng.uniform( 0, 255)); 
        drawContours(draw,result_contours,i,color, - 1); 
    } 
     return result_contours; 
} 
 //计算轮廓的圆的特性 
 float calculateCircularity(VP contour) 
{ 
    Point2f center; 
     float radius  =  0; 
    minEnclosingCircle((Mat)contour,center,radius); 
     //以最小外接圆半径作为数学期望，计算轮廓上各点到圆心距离的标准差 
     float fsum  =  0; 
     float fcompare  =  0; 
     for ( int i = 0;i <contour.size();i ++) 
    {    
        Point2f ptmp  = contour[i]; 
         float fdistenct  = sqrt(( float)((ptmp.x  - center.x) *(ptmp.x  - center.x) +(ptmp.y  - center.y) *(ptmp.y -center.y))); 
         float fdiff  = abs(fdistenct  - radius); 
        fsum  = fsum  + fdiff; 
    } 
    fcompare  = fsum /( float)contour.size(); 
     return fcompare; 
} 
 //select_shape 
vector <VP > selectShapeCircularity(Mat src,Mat & draw,vector <VP > contours, float minvalue, float maxvalue) 
{ 
    vector <VP > result_contours; 
    draw  = Mat : :zeros(src.rows,src.cols,CV_8UC3); 
     for ( int i = 0;i <contours.size();i ++) 
    { 
         float fcompare  = calculateCircularity(contours[i]); 
         if (fcompare  > =minvalue  && fcompare  < =maxvalue) 
        { 
            result_contours.push_back(contours[i]); 
        } 
    } 
     for ( int i = 0;i <result_contours.size();i ++) 
    { 
        Scalar  color   = Scalar(rng.uniform( 0, 255),rng.uniform( 0, 255),rng.uniform( 0, 255)); 
        drawContours(draw,result_contours,i,color, - 1); 
    } 
     return result_contours; 
} 
 int _tmain( int argc, _TCHAR * argv[]) 
{     
    Mat src; 
    Mat gray; 
    Mat thresh; 
    Mat draw_connection; 
    Mat draw_area; 
    Mat draw_circle; 
    vector <VP >contours_connection;     
    vector <VP >contours_area; 
    vector <VP >contours_circle; 
    vector <VP >contours_tmp; 
     //read_image (Image1, 'F:/未来项目/钢管识别/FindTube/FindTube/1.jpg') 
    src  = imread( "1.jpg"); 
     //rgb1_to_gray (Image1, GrayImage) 
    cvtColor(src,gray,COLOR_BGR2GRAY); 
     //threshold (GrayImage, Regions, 43, 111) 
    threshold2(gray,thresh, 43, 111); 
     //connection (Regions, ConnectedRegions) 
    contours_connection  = connection2(thresh.clone(),draw_connection); 
     //select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 150, 666) 
    contours_area  = selectShapeArea(thresh.clone(),draw_area,contours_connection, 150, 666); 
     //select_shape (SelectedRegions, SelectedRegions1, 'circularity', 'and', 0.45, 1) 
    contours_circle  = selectShapeCircularity(thresh.clone(),draw_circle,contours_area, 1, 6); 
     //显示结果 
    imshow( "src",src); 
    imshow( "thresh",thresh); 
    imshow( "draw_connection",draw_connection); 
    imshow( "draw_area",draw_area); 
    imshow( "draw_circle",draw_circle); 
    waitKey(); 
} 