OpenCV Tutorials —— Convex Hull

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void convexHull(InputArray points, OutputArray hull, bool clockwise=false, bool returnPoints=true )

Parameters:

• points – Input 2D point set, stored in std::vector or Mat.
• hull – Output convex hull. It is either an integer vector of indices or vector of points. In the first case, the hull elements are 0-based indices of the convex hull points in the original array (since the set of convex hull points is a subset of the original point set). In the second case,hull elements are the convex hull points themselves.
• hull_storage – Output memory storage in the old API (cvConvexHull2 returns a sequence containing the convex hull points or their indices).
• clockwise – Orientation flag. If it is true, the output convex hull is oriented clockwise. Otherwise, it is oriented counter-clockwise. The assumed coordinate system has its X axis pointing to the right, and its Y axis pointing upwards.
• orientation – Convex hull orientation parameter in the old API, CV_CLOCKWISE orCV_COUNTERCLOCKWISE.
• returnPoints – Operation flag. In case of a matrix, when the flag is true, the function returns convex hull points. Otherwise, it returns indices of the convex hull points. When the output array is std::vector, the flag is ignored, and the output depends on the type of the vector:std::vector<int> implies returnPoints=true, std::vector<Point> implies returnPoints=false.

Code

#include "stdafx.h"

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>

using namespace cv;
using namespace std;

Mat src; Mat src_gray;
int thresh = 100;
int max_thresh = 255;
RNG rng(12345);

/// Function header
void thresh_callback(int, void* );

/** @function main */
int main( int argc, char** argv )
{
	/// Load source image and convert it to gray
	src = imread( "img2.jpg", 1 );

	/// Convert image to gray and blur it
	cvtColor( src, src_gray, CV_BGR2GRAY );
	blur( src_gray, src_gray, Size(3,3) );

	/// Create Window
	char* source_window = "Source";
	namedWindow( source_window, CV_WINDOW_AUTOSIZE );
	imshow( source_window, src );

	createTrackbar( " Threshold:", "Source", &thresh, max_thresh, thresh_callback );
	thresh_callback( 0, 0 );

	waitKey(0);
	return(0);
}

/** @function thresh_callback */
void thresh_callback(int, void* )
{
	Mat src_copy = src.clone();
	Mat threshold_output;
	vector<vector<Point> > contours;
	vector<Vec4i> hierarchy;

	/// Detect edges using Threshold
	threshold( src_gray, threshold_output, thresh, 255, THRESH_BINARY );

	/// Find contours
	findContours( threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );

	/// Find the convex hull object for each contour
	vector<vector<Point> >hull( contours.size() );
	for( int i = 0; i < contours.size(); i++ )
	{  convexHull( Mat(contours[i]), hull[i], false ); }

	/// Draw contours + hull results
	Mat drawing = Mat::zeros( threshold_output.size(), CV_8UC3 );
	for( int i = 0; i< contours.size(); i++ )
	{
		Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );
		drawContours( drawing, contours, i, color, 1, 8, vector<Vec4i>(), 0, Point() );
		drawContours( drawing, hull, i, color, 1, 8, vector<Vec4i>(), 0, Point() );
	}

	/// Show in a window
	namedWindow( "Hull demo", CV_WINDOW_AUTOSIZE );
	imshow( "Hull demo", drawing );
}