recognise colours in 3x3 grid

edit

there is some solutions on the net about "Solving Rubik's Cube" or "Locating Rubik's Cube" using OpenCV like this. Maybe you can find better code sample.But i want to share a simple code to show with just a simple OpenCV code you will get some result like

the code is modified version of squares.cpp

#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"

using namespace cv;
using namespace std;

// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2
static double angle( Point pt1, Point pt2, Point pt0 )
{
    double dx1 = pt1.x - pt0.x;
    double dy1 = pt1.y - pt0.y;
    double dx2 = pt2.x - pt0.x;
    double dy2 = pt2.y - pt0.y;
    return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}

static void drawSquares( Mat& image, const vector<vector<Point> >& squares )
{
    for( size_t i = 0; i < squares.size(); i++ )
    {
        const Point* p = &squares[i][0];
        int n = (int)squares[i].size();
        int shift = 1;

        Rect r=boundingRect( Mat(squares[i]));
        r.x = r.x + r.width / 4;
        r.y = r.y + r.height / 4;
        r.width = r.width / 2;
        r.height = r.height / 2;

        Mat roi = image(r);
        Scalar color = mean(roi);
        polylines(image, &p, &n, 1, true, color, 2, LINE_AA, shift);

        Point center( r.x + r.width/2, r.y + r.height/2 );
        ellipse( image, center, Size( r.width/2, r.height/2), 0, 0, 360, color, 2, LINE_AA );
    }
}

// returns sequence of squares detected on the image.
// the sequence is stored in the specified memory storage
static void findSquares( const Mat& image, vector<vector<Point> >& squares , bool inv=false)
{
    squares.clear();

    Mat gray,gray0;

    vector<vector<Point> > contours;

    cvtColor(image,gray0,COLOR_BGR2GRAY);
    GaussianBlur(gray0, gray0, Size(7,7), 1.5, 1.5);
    Canny(gray0,gray, 0, 30, 3);

    // find contours and store them all as a list
    findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);

    vector<Point> approx;

    // test each contour
    for( size_t i = 0; i < contours.size(); i++ )
    {
        // approximate contour with accuracy proportional
        // to the contour perimeter
        approxPolyDP(Mat(contours[i]), approx, 9, true);

        // square contours should have 4 vertices after approximation
        // relatively large area (to filter out noisy contours)
        // and be convex.
        // Note: absolute value of an area is used because
        // area may be positive or negative - in accordance with the
        // contour orientation
        if( approx.size() == 4 &&
                fabs(contourArea(Mat(approx))) > 5 &&
                isContourConvex(Mat(approx)) )
        {
            double maxCosine = 0;

            for( int j = 2; j < 5; j++ )
            {
                // find the maximum cosine of the angle between joint edges
                double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1]));
                maxCosine = MAX(maxCosine, cosine);
            }

            // if cosines of all angles are small
            // (all angles are ~90 degree) then write quandrange
            // vertices to resultant sequence
            if( maxCosine < 0.3 )
                squares.push_back(approx);
        }
    }
}

int main()
{
    VideoCapture cap(0); // opens default webcam

    if (!cap.isOpened())
    {
        return -1;
    }

    Mat frame;
    vector<vector<Point> > squares;

    for (;;)
    {
        cap >> frame;

        if (frame.empty())
        {
            return -1;
        }
        findSquares(frame, squares);
        drawSquares(frame, squares);
        imshow("Rubic Detection Demo", frame);
        waitKey ...