Why do I receive breakpoints by findContours? - c++

Question

I've been trying to set up a program that uses HSV to detect a specific colour and place a rectangle around the biggest area found of said colour. I am having problems when i get to the vectors and the "findContours" function, which stops the program with an error stating "xxx.exe has triggered a break point".
This only happens when I insert the line
findContours(dilatedBlue,contours,hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE);
I'm a rookie when it comes to OpenCV and C++ but I'm hoping someone will be able to help. I'm using windows 7 x64, Visual Studio 2012 and OpenCV 2.4.8.
My full code is what follows:
#include "stdafx.h"
#include <opencv2/core/core.hpp> // Basic OpenCV structures (cv::Mat, Scalar)
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/opencv.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace cv;
int _tmain(int argc, _TCHAR* argv[])
{
VideoCapture cap(0); // open the default camera
if(!cap.isOpened()) // check if we succeeded
return -1;
// Declare Local Variables
int Quit = 0;
Mat imageDiff;
Mat HSVMatrix[3];
Mat erodedBlue;
Mat dilatedBlue;
//Start of search/shoot routine
while( Quit != 'q' ) // For as long as User wishes to continue...
{
Mat image;
cap >> image; // get a new frame from camera
imshow("Original", image);
//GaussianBlur(image, image, Size(3,3), 1.5, 1.5); // Setting up a Gaussian blur using 5x5 grid
cvtColor(image, imageDiff, CV_BGR2HSV);
split(imageDiff,HSVMatrix);
//Setting up saturation values for colour blue
threshold(HSVMatrix[0],HSVMatrix[0],130,255,THRESH_TOZERO_INV); // High value of colour - Dynamic changing of variable to select mode 130
threshold(HSVMatrix[0],HSVMatrix[0],75,255,THRESH_BINARY); // Low value of colour 75
threshold(HSVMatrix[1],HSVMatrix[1],255,255,THRESH_TOZERO_INV); // High saturation value - Modify for varying levels of light
threshold(HSVMatrix[1],HSVMatrix[1],100,255,THRESH_BINARY); // Low saturation value
HSVMatrix[2]=HSVMatrix[1]&HSVMatrix[0];
imshow("HSVblue", HSVMatrix[2]); // Displays binarised image
erode(HSVMatrix[2], HSVMatrix[2], Mat(), Point(-1, -1), 2, 1, 1);
erode(HSVMatrix[2], erodedBlue, Mat(), Point(-1, -1), 2, 1, 1);
imshow("Eroded-Blue", erodedBlue);
dilate(erodedBlue, dilatedBlue, Mat(), Point(-1, -1), 2, 1, 1);
imshow("Dilated-Blue", dilatedBlue);
vector<vector<Point> > contours; // Temporary variables used to hold contour information
vector<Point> approx;
vector<Vec4i> hierarchy;
vector<Rect> boundRect(contours.size());
findContours(dilatedBlue,contours,hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE);
for (int i = 0; i < contours.size(); i++)
{
approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true) * 0.02, true); // Calculation of contours and their approximate size and sides
}
for (int i = 0; i < contours.size(); i++)
{
if ((approx.size() == 4) && (fabs(contourArea(Mat(approx))) > 100)) // The properties that have to be fulfilled in order for the object to be recognized by the computer
{
Rect outline; // If the properties have been fulfilled and the object has been recognized, display an outline around the object
outline = boundingRect(approx);
rectangle(image,Rect(outline),Scalar(0, 255, 255),5,8,0); // The properties of the outline: the colour[bgr] and thickness
}
}
imshow("Target", image);
}
Quit = cvWaitKey(1); // The program waits for the key "q" to be pressed to exit
}
cap.release();
return 0;
}