Reading rubik cube colors with Opencv

I wrote a C ++ program using OpenCV that can detect and highlight the edges of any object from a live video. But now I don't know how to extract the four corners of a cube from the many edges that show up in the video. So I am looking for some help here.

Here is the link of the article I am using as a guide for my project. http://www.cs.ubc.ca/~andrejk/525project/525report.pdf You can find the code for this article at the link below. This is written in Python. (I'm using C ++ and I don't know Python) http://www.cs.ubc.ca/~andrejk/525project/cubefinder.py

According to the article, the next step is to "segment the edge with an adaptive threshold." Which I really don't understand. And also I don't know how to extract the corners of the cube then.

A quick overview of the method I used is as follows. 1. Webcam login 2. Apply Laplacian filter 3. Apply Hough line transform.

I get the following result.

Result

code

using namespace std;
using namespace cv;

Mat laplacianFilter(Mat image)
{
Mat hImage;

GaussianBlur(image,hImage,Size(3,3),0,0,BORDER_DEFAULT);
cvtColor(hImage,hImage,CV_RGB2GRAY);
Laplacian(hImage,hImage,CV_16SC1,3,1,0,BORDER_DEFAULT);
convertScaleAbs(hImage,hImage,1,0);

return hImage;
}

Mat hghTransform(Mat image, Mat &image2)
{
Mat lImage;

Canny(image,image,50,200,3);
cvtColor(image,lImage,CV_GRAY2BGR);

    vector<Vec4i> lines;
    HoughLinesP(image, lines, 1, CV_PI/180, 50, 50, 10 );
    for( size_t i = 0; i < lines.size(); i++ )
    {
        Vec4i l = lines[i];
        line( image2, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0,255,0), 3, CV_AA);
    }

return lImage;
}


int main()
{
int c;

VideoCapture cap(0);

Mat image;
Mat image2;

namedWindow("hghtransform");
namedWindow("laplacianfilter");
namedWindow("cannyOutput");

while(1)
{
    cap>>image;
    cap>>image2;

    //Output
    imshow("laplacianfilter",laplacianFilter(image));
    imshow("cannyOutput",hghTransform(laplacianFilter(image),image2));
    imshow("hghtransform",image2);

    c=waitKey(33);

    if(c==27)
        return 0;

}

return 0;
}

      

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1 answer


The adaptive threshold will give you a clear edge line that will allow you to get the 9 squares of the rubik side correctly.

You can see a decent comparison of global versus adaptive threshold here:
here: https://sites.google.com/site/qingzongtseng/adaptivethreshold

original image:
enter image description here

global threshold:
enter image description here



adaptive threshold:
enter image description here

To the corner, I'm not sure if it was stated in the document, but I would do something like:
==> search area, for example 1

, 2

, 3

, 4

for upper-left

, upper-right

, lower-left

and lower-right

, respectively.

==> with a pattern matching algorithm.
enter image description here

hope this helps.

Note: You may want to have a background with less noise. =)

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