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you can use the function below

// calculates distance between two points
static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

also you can see an example code using this function here

to calculate distance between two points you can use the function below

// calculates distance between two points
static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

also you can see an example code using this function here

to calculate distance between two points you can use the function below

static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

also you can see an example code using this function here

EDIT : i learned from LBerger that norm function do it.

#include <opencv2/highgui.hpp>
#include <iostream>

using namespace cv;
using namespace std;

// calculates distance between two points
static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

int main( int argc, char** argv )
{
Point pt0(200,200);
Point pt1(100,100);

cout << "distanceBtwPoints result : " << distanceBtwPoints(pt0,pt1) << endl;

cout << "norm result " << norm(pt0-pt1);

}

to calculate distance between two points you can use the function below

static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

also you can see an example code using this function here

EDIT : i learned from LBerger that norm function do it.

#include <opencv2/highgui.hpp>
#include <iostream>

using namespace cv;
using namespace std;

// calculates distance between two points
static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

int main( int argc, char** argv )
{
Point pt0(200,200);
Point pt1(100,100);

cout << "distanceBtwPoints result : " << distanceBtwPoints(pt0,pt1) << endl;

cout << "norm result " << norm(pt0-pt1);

}

EDIT 2 :

look at the code below. maybe it help to get better result about finding edges.

#include "opencv2/opencv.hpp"
using namespace cv;
int main(int, char**)
{
    VideoCapture cap(0); // open the default camera
    if(!cap.isOpened())  // check if we succeeded
        return -1;
    Mat edges;
    namedWindow("edges",1);
    for(;;)
    {
        Mat frame;
        cap >> frame; // get a new frame from camera
        cvtColor(frame, edges, COLOR_BGR2GRAY);
        GaussianBlur(edges, edges, Size(7,7), 1.5, 1.5);
        Canny(edges, edges, 0, 30, 3);
        imshow("edges", edges);
        if(waitKey(30) >= 0) break;
    }
    // the camera will be deinitialized automatically in VideoCapture destructor
    return 0;
}

to calculate distance between two points you can use the function below

static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

also you can see an example code using this function here

EDIT : i learned from LBerger that norm function do it.

#include <opencv2/highgui.hpp>
#include <iostream>

using namespace cv;
using namespace std;

// calculates distance between two points
static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

int main( int argc, char** argv )
{
Point pt0(200,200);
Point pt1(100,100);

cout << "distanceBtwPoints result : " << distanceBtwPoints(pt0,pt1) << endl;

cout << "norm result " << norm(pt0-pt1);

}

EDIT 2 :

look at the code below. maybe it help to get better result about finding ~~edges.~~edges. next step will be findContours. you can find many examples about using findContours.

#include "opencv2/opencv.hpp"
using namespace cv;
int main(int, char**)
{
    VideoCapture cap(0); // open the default camera
    if(!cap.isOpened())  // check if we succeeded
        return -1;
    Mat edges;
    namedWindow("edges",1);
    for(;;)
    {
        Mat frame;
        cap >> frame; // get a new frame from camera
        cvtColor(frame, edges, COLOR_BGR2GRAY);
        GaussianBlur(edges, edges, Size(7,7), 1.5, 1.5);
        Canny(edges, edges, 0, 30, 3);
        imshow("edges", edges);
        if(waitKey(30) >= 0) break;
    }
    // the camera will be deinitialized automatically in VideoCapture destructor
    return 0;
}

to calculate distance between two points you can use the function below

static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

also you can see an example code using this function here

EDIT : i learned from LBerger that norm function do it.

#include <opencv2/highgui.hpp>
#include <iostream>

using namespace cv;
using namespace std;

// calculates distance between two points
static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

int main( int argc, char** argv )
{
Point pt0(200,200);
Point pt1(100,100);

cout << "distanceBtwPoints result : " << distanceBtwPoints(pt0,pt1) << endl;

cout << "norm result " << norm(pt0-pt1);

}

EDIT 2 :

look at the code below. maybe it help to get better result about finding edges. next step will be findContours. you can find many examples about using findContours. like http://answers.opencv.org/question/71105.

#include "opencv2/opencv.hpp"
using namespace cv;
int main(int, char**)
{
    VideoCapture cap(0); // open the default camera
    if(!cap.isOpened())  // check if we succeeded
        return -1;
    Mat edges;
    namedWindow("edges",1);
    for(;;)
    {
        Mat frame;
        cap >> frame; // get a new frame from camera
        cvtColor(frame, edges, COLOR_BGR2GRAY);
        GaussianBlur(edges, edges, Size(7,7), 1.5, 1.5);
        Canny(edges, edges, 0, 30, 3);
        imshow("edges", edges);
        if(waitKey(30) >= 0) break;
    }
    // the camera will be deinitialized automatically in VideoCapture destructor
    return 0;
}

to calculate distance between two points you can use the function below

static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

also you can see an example code using this function here

EDIT : i learned from LBerger that norm function do it.

#include <opencv2/highgui.hpp>
#include <iostream>

using namespace cv;
using namespace std;

// calculates distance between two points
static double distanceBtwPoints(const cv::Point a, const cv::Point b)
{
    double xDiff = a.x - b.x;
    double yDiff = a.y - b.y;

    return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}

int main( int argc, char** argv )
{
Point pt0(200,200);
Point pt1(100,100);

cout << "distanceBtwPoints result : " << distanceBtwPoints(pt0,pt1) << endl;

cout << "norm result " << norm(pt0-pt1);

}

EDIT 2 2,3 :

look at the code below. maybe it ~~help to get better result about finding edges. next step will be findContours.~~ give you another idea using findContours and boundingRect you can ~~find many examples about using findContours~~ get widht and heigth of square objects like ~~http://answers.opencv.org/question/71105.~~result image:

image description

#include "opencv2/opencv.hpp"
 using namespace cv;
using namespace std;

int main(int, char**)
{
    VideoCapture cap(0); // open the default camera
    if(!cap.isOpened())  // check if we succeeded
        return -1;
    Mat edges;
    namedWindow("edges",1);
    for(;;)
    {
        Mat frame;
        cap >> frame; // get a new frame from camera
        cvtColor(frame, edges, COLOR_BGR2GRAY);
        GaussianBlur(edges, edges, Size(7,7), 1.5, 1.5);
        Canny(edges, edges, 0, 30, 50, 3);

        vector<vector<Point> > contours;
        findContours(edges, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);

        for( size_t i = 0; i < contours.size(); i++ )
        {
            Rect minRect = boundingRect(contours[i]);

            if(minRect.width > 150 & minRect.height > 150 )
            {
            rectangle(frame,minRect,Scalar(0,0,255));
            putText(frame,format("width = %d , height = %d",minRect.width,minRect.height), Point(minRect.x,minRect.y),
                    FONT_HERSHEY_PLAIN, 1, Scalar(0,255,0));
            }

        }
        imshow("edges", edges);
frame);
        if(waitKey(30) >= 0) break;
    }
    // the camera will be deinitialized automatically in VideoCapture destructor
    return 0;
}