在opencv C++函數中查找凸面缺陷的點

Question

我想恢復凸面缺陷的點，但函數只返回我的整數，你能給我一個關於如何找到這些點的提示嗎？

vector<vector<Point> >hull2(contours.size()); 
      vector<vector<int>> hull(contours.size()); 
std::vector<cv::Vec4i> convexityDefectsSet;  

    for(int i = 0; i < contours.size(); i++) { 
     convexHull(Mat(contours[i]), hull[i], false); 
     convexHull(Mat(contours[i]), hull2[i], false); 
     if (contours[i].size() > 3) { 
     cv::convexityDefects(Mat(contours[i]), hull[i], convexityDefectsSet); 

     for (int cDefIt = 0; cDefIt < convexityDefectsSet.size(); cDefIt++) { 

      int startIdx = convexityDefectsSet[cDefIt].val[0]; 

      int endIdx = convexityDefectsSet[cDefIt].val[1]; 

      int defectPtIdx = convexityDefectsSet[cDefIt].val[2]; 

      double depth = static_cast<double>(convexityDefectsSet[cDefIt].val[3])/256.0; 

      std::cout << startIdx << ' ' << endIdx << ' ' << defectPtIdx << ' ' << depth << '\n' << '\n' << std::endl; 

      Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255)); 
      Point2f p(defectPtIdx, defectPtIdx); 
      circle(frame, p , 10, color, 2, 8, 0); 
     } 
     }} 

Answer 1

按照documentation：

In C++ and the new Python/Java interface each convexity defect is represented 
as 4-element integer vector [...]: (start_index, end_index, farthest_pt_index, 
fixpt_depth), where indices are 0-based indices in the original contour of 
the convexity defect... 

它們對應於用於生成的凸包，即，您的contours[i]變量在原始輪廓指標。 （應該檢測手（顏色檢測器需要進行調諧）和搜索CONV缺陷）： 例如，與所獲得的第一點的座標

cv::Point start = contours.at(startIdx); 

Answer 2

我認爲這我的一段代碼。但你可以用它作爲你的代碼的基礎：

#include <stdlib.h> 
#include <stdio.h> 
#include <iostream> 
#include <ctype.h> 
#include <time.h> 

#include <opencv2\imgproc\imgproc.hpp> 
#include <opencv2\video\tracking.hpp> 
#include <opencv2\highgui\highgui.hpp> 

using namespace cv; 
using namespace std; 

// Detect Skin from YCrCb 
Mat DetectYCrCb(Mat img, Scalar min, Scalar max) { 
    Mat skin; 
    cvtColor(img, skin, cv::COLOR_BGR2YCrCb); 
    inRange(skin, min, max, skin); 
    Mat rect_12 = getStructuringElement(cv::MORPH_RECT, Size(12,12) , Point(6,6)); 
    erode(skin, skin, rect_12,Point(),1); 
    Mat rect_6 = getStructuringElement(cv::MORPH_RECT, Size(6,6) , Point(3,3)); 
    dilate(skin,skin,rect_6,Point(),2); 
    return skin;  
} 

void DetectContour(Mat img){ 
    Mat drawing = Mat::zeros(img.size(), CV_8UC3); 
    vector<vector<Point> > contours; 
    vector<vector<Point> > bigContours; 
    vector<Vec4i> hierarchy; 

    findContours(img,contours, hierarchy, cv::RETR_LIST, cv::CHAIN_APPROX_SIMPLE, Point()); 

    if(contours.size()>0) 
    { 
     vector<std::vector<int> >hull(contours.size()); 
     vector<vector<Vec4i>> convDef(contours.size()); 
     vector<vector<Point>> hull_points(contours.size()); 
     vector<vector<Point>> defect_points(contours.size()); 


     for(int i = 0; i < contours.size(); i++) 
     { 
      if(contourArea(contours[i])>5000) 
      { 
       convexHull(contours[i], hull[i], false); 
       convexityDefects(contours[i],hull[i], convDef[i]); 

       for(int k=0;k<hull[i].size();k++) 
       {   
        int ind=hull[i][k]; 
        hull_points[i].push_back(contours[i][ind]); 
       } 

       for(int k=0;k<convDef[i].size();k++) 
       {   
        if(convDef[i][k][3]>20*256) // filter defects by depth 
        { 
        int ind_0=convDef[i][k][0]; 
        int ind_1=convDef[i][k][1]; 
        int ind_2=convDef[i][k][2]; 
        defect_points[i].push_back(contours[i][ind_2]); 
        cv::circle(drawing,contours[i][ind_0],5,Scalar(0,255,0),-1); 
        cv::circle(drawing,contours[i][ind_1],5,Scalar(0,255,0),-1); 
        cv::circle(drawing,contours[i][ind_2],5,Scalar(0,0,255),-1); 
        cv::line(drawing,contours[i][ind_2],contours[i][ind_0],Scalar(0,0,255),1); 
        cv::line(drawing,contours[i][ind_2],contours[i][ind_1],Scalar(0,0,255),1); 
        } 
       } 

       drawContours(drawing, contours, i, Scalar(0,255,0), 1, 8, vector<Vec4i>(), 0, Point()); 
       drawContours(drawing, hull_points, i, Scalar(255,0,0), 1, 8, vector<Vec4i>(), 0, Point()); 
      } 
     } 
    } 
    imshow("Hull demo", drawing); 
} 


int main(int argc, char** argv) 
{ 
    Mat frame,copyFrame; 
    VideoCapture capture(0); 
    namedWindow("Hull demo", cv::WINDOW_AUTOSIZE); 
    namedWindow("Video", cv::WINDOW_AUTOSIZE); 
    if (capture.isOpened()){ 
     while(true) 
     { 
      capture >> frame; 
      imshow("Video", frame); 

      Mat skinYCrCb = DetectYCrCb(frame,Scalar(0, 100, 80), Scalar(255, 185, 135)); 

      DetectContour(skinYCrCb); 

      int c = waitKey(10); 
      if((char)c == 27) 
      { 
       break; 
      } 
     } 
    } 
    cv::destroyAllWindows(); 
    return 0; 
}