How to find the corners of a Rect object in openCV?

Question

I am using openCV library on the android platform. I have successfully detected the largest rectangle from the image but since my application will be used for the scanning purpose ,i want to have the perspective change functionality as well.

I know,how to apply perspectiveTransform and warpPerspectiveTransform,but for that i will need corners of the rectangle for the source points.

It seems very easy to find the corners given the fact we have the coordinates of the first corner(Top-left) and width/height associated with the Rect object but the problem is ,for a rotated rectangle(usual boundingRect but sides not parallel to axis) ,these values are very different.In this case it stores the values corresponding to an another rectangle having sides parallel to axis and covering the rotated rectangle so that makes me unable to detect corners of the actual rectangle.

Also i want to do a comparison between these two algorithms for detecting a sheet from the image.

1. Canny edge -> Largest contour -> largest rectangle -> find corners -> perspective change

2. Canny edge-> Hough lines -> intersection of the lines -> perspective change

The thing that i want to ask is given if we have a Rect object ,how to get all the corners of that rectangle ?

Thanks in advance.

Answer 1

I am very exciting to answer my question ! It was easy but it happens when u just begin with something with not so proper relevant documentation .

I was trying hard to get the corners of a general rectangle which was not defined in the implementation of openCV and hence was almost impossible.

I followed the standard code on stackoverflow for the largest Square detection. and corners can be easily find out using the approxCurve itself.

//convert the image to black and white

        Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BGR2GRAY);

        //convert the image to black and white does (8 bit)
        Imgproc.Canny(imgSource, imgSource, 50, 50);

        //apply gaussian blur to smoothen lines of dots
        Imgproc.GaussianBlur(imgSource, imgSource, new  org.opencv.core.Size(5, 5), 5);

        //find the contours
        List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
        Imgproc.findContours(imgSource, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);

        double maxArea = -1;
        int maxAreaIdx = -1;
        Log.d("size",Integer.toString(contours.size()));
        MatOfPoint temp_contour = contours.get(0); //the largest is at the index 0 for starting point
        MatOfPoint2f approxCurve = new MatOfPoint2f();
        MatOfPoint largest_contour = contours.get(0);
        //largest_contour.ge
        List<MatOfPoint> largest_contours = new ArrayList<MatOfPoint>();
        //Imgproc.drawContours(imgSource,contours, -1, new Scalar(0, 255, 0), 1);

        for (int idx = 0; idx < contours.size(); idx++) {
            temp_contour = contours.get(idx);
            double contourarea = Imgproc.contourArea(temp_contour);
            //compare this contour to the previous largest contour found
            if (contourarea > maxArea) {
                //check if this contour is a square
                MatOfPoint2f new_mat = new MatOfPoint2f( temp_contour.toArray() );
                int contourSize = (int)temp_contour.total();
                MatOfPoint2f approxCurve_temp = new MatOfPoint2f();
                Imgproc.approxPolyDP(new_mat, approxCurve_temp, contourSize*0.05, true);
                if (approxCurve_temp.total() == 4) {
                    maxArea = contourarea;
                    maxAreaIdx = idx;
                    approxCurve=approxCurve_temp;
                    largest_contour = temp_contour;
                }
            }
        }

       Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BayerBG2RGB);
       sourceImage =Highgui.imread(Environment.getExternalStorageDirectory().
                 getAbsolutePath() +"/scan/p/1.jpg");
       double[] temp_double;
       temp_double = approxCurve.get(0,0);       
       Point p1 = new Point(temp_double[0], temp_double[1]);
       //Core.circle(imgSource,p1,55,new Scalar(0,0,255));
       //Imgproc.warpAffine(sourceImage, dummy, rotImage,sourceImage.size());
       temp_double = approxCurve.get(1,0);       
       Point p2 = new Point(temp_double[0], temp_double[1]);
      // Core.circle(imgSource,p2,150,new Scalar(255,255,255));
       temp_double = approxCurve.get(2,0);       
       Point p3 = new Point(temp_double[0], temp_double[1]);
       //Core.circle(imgSource,p3,200,new Scalar(255,0,0));
       temp_double = approxCurve.get(3,0);       
       Point p4 = new Point(temp_double[0], temp_double[1]);
      // Core.circle(imgSource,p4,100,new Scalar(0,0,255));
       List<Point> source = new ArrayList<Point>();
       source.add(p1);
       source.add(p2);
       source.add(p3);
       source.add(p4);
       Mat startM = Converters.vector_Point2f_to_Mat(source);
       Mat result=warp(sourceImage,startM);
       return result;

and the function used for the perspective transform is given below :

 public Mat warp(Mat inputMat,Mat startM) {
            int resultWidth = 1000;
            int resultHeight = 1000;

            Mat outputMat = new Mat(resultWidth, resultHeight, CvType.CV_8UC4);



            Point ocvPOut1 = new Point(0, 0);
            Point ocvPOut2 = new Point(0, resultHeight);
            Point ocvPOut3 = new Point(resultWidth, resultHeight);
            Point ocvPOut4 = new Point(resultWidth, 0);
            List<Point> dest = new ArrayList<Point>();
            dest.add(ocvPOut1);
            dest.add(ocvPOut2);
            dest.add(ocvPOut3);
            dest.add(ocvPOut4);
            Mat endM = Converters.vector_Point2f_to_Mat(dest);      

            Mat perspectiveTransform = Imgproc.getPerspectiveTransform(startM, endM);

            Imgproc.warpPerspective(inputMat, 
                                    outputMat,
                                    perspectiveTransform,
                                    new Size(resultWidth, resultHeight), 
                                    Imgproc.INTER_CUBIC);

            return outputMat;
        }