Find point of convexity defects in opencv c++ function - c++

Question

I am trying to recover the point of convexity defect, but the function only returns me integer, can you give me a hint on how to find these points?
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

I think this my piece of code (should detect hand (color detector need to be tuned) and search conv. defects). But you can use it as base for your code:
#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;
}

Answer 2

According to the 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...
They correspond to indices in the original contour that was used to generate the convex hull, i.e., your contours[i] variable.
For example, the coordinates of the first point are obtained with:
cv::Point start = contours.at(startIdx);