// =================
// || Worksheet 4
// || In this example, we are going to build the famous Canny edge detector.
// =================

// for comparison, see:
//
// https://en.wikipedia.org/wiki/Canny_edge_detector

#include <opencv2/core.hpp>
#include <opencv2/core/utility.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <iostream>

#include <iostream>

using namespace std;
using namespace cv;

int worksheetfour( Mat& colorImage )
{
    // Part one: Read in the image.

    //      we'll do everything in greyscale for now.
    
    // Part two: take the horizontal derivatives
    
    //      design a convolution kernel that takes discretizes the 1D derivative along the x axis.
    
    // Part three: take the vertical derivatives
    
    //      apply the same kernel to the y axis. this output should be stored in a seperate matrix
    
    //      Hint: Do i need a new kernel? what about matrix transpose?
    //      http://docs.opencv.org/modules/core/doc/operations_on_arrays.html
    
    // Part four: sum the squares of the derivative images, take the square root, and store it in a new image.
    
    //  we saw how to do basic operators on image pixels earlier. Hint: might need to use the c++ function 'sqrt'

    
    // Part five: display the output image.
    
    //      easy!
    
    
    return 0;
}