Пример #1
0
  /**
   * Locate rectangles in an image
   *
   * @param grayImage Grayscale image
   * @return Rectangle locations
   */
  public RectangleLocationResult locateRectangles(Mat grayImage) {
    Mat gray = grayImage.clone();

    // Filter out some noise
    Filter.downsample(gray, 2);
    Filter.upsample(gray, 2);

    Mat cacheHierarchy = new Mat();
    Mat grayTemp = new Mat();
    List<Rectangle> rectangles = new ArrayList<>();
    List<Contour> contours = new ArrayList<>();

    Imgproc.Canny(gray, grayTemp, 0, THRESHOLD_CANNY, APERTURE_CANNY, true);
    Filter.dilate(gray, 2);

    List<MatOfPoint> contoursTemp = new ArrayList<>();
    // Find contours - the parameters here are very important to compression and retention
    Imgproc.findContours(
        grayTemp, contoursTemp, cacheHierarchy, Imgproc.CV_RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);

    // For each contour, test whether the contour is a rectangle
    // List<Contour> contours = new ArrayList<>();
    MatOfPoint2f approx = new MatOfPoint2f();
    for (MatOfPoint co : contoursTemp) {
      MatOfPoint2f matOfPoint2f = new MatOfPoint2f(co.toArray());
      Contour c = new Contour(co);

      // Attempt to fit the contour to the best polygon
      Imgproc.approxPolyDP(
          matOfPoint2f, approx, c.arcLength(true) * EPLISON_APPROX_TOLERANCE_FACTOR, true);

      Contour approxContour = new Contour(approx);

      // Make sure the contour is big enough, CLOSED (convex), and has exactly 4 points
      if (approx.toArray().length == 4
          && Math.abs(approxContour.area()) > 1000
          && approxContour.isClosed()) {

        // TODO contours and rectangles array may not match up, but why would they?
        contours.add(approxContour);

        // Check each angle to be approximately 90 degrees
        double maxCosine = 0;
        for (int j = 2; j < 5; j++) {
          double cosine =
              Math.abs(
                  MathUtil.angle(
                      approx.toArray()[j % 4], approx.toArray()[j - 2], approx.toArray()[j - 1]));
          maxCosine = Math.max(maxCosine, cosine);
        }

        if (maxCosine < MAX_COSINE_VALUE) {
          // Convert the points to a rectangle instance
          rectangles.add(new Rectangle(approx.toArray()));
        }
      }
    }

    return new RectangleLocationResult(contours, rectangles);
  }
Пример #2
0
  private static Mat findLargestRectangle(Mat original_image) {
    Mat imgSource = original_image.clone();

    // 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 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;
    MatOfPoint temp_contour = contours.get(0); // the largest is at the
    // index 0 for starting
    // point
    MatOfPoint2f approxCurve = new MatOfPoint2f();
    List<MatOfPoint> largest_contours = new ArrayList<MatOfPoint>();
    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();
        Imgproc.approxPolyDP(new_mat, approxCurve, contourSize * 0.05, true);
        if (approxCurve.total() == 4) {
          maxArea = contourarea;
          largest_contours.add(temp_contour);
        }
      }
    }
    MatOfPoint temp_largest = largest_contours.get(largest_contours.size() - 1);
    largest_contours = new ArrayList<MatOfPoint>();

    largest_contours.add(temp_largest);

    // Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BayerBG2RGB);
    Imgproc.drawContours(original_image, largest_contours, -1, new Scalar(0, 255, 0), 10);

    // Mat perspectiveTransform = new Mat(3, 3, CvType.CV_32FC1);
    // Imgproc.warpPerspective(original_image, imgSource,
    // perspectiveTransform, new Size(300,300));

    Highgui.imwrite(output, original_image);

    // create the new image here using the largest detected square

    // Toast.makeText(getApplicationContext(), "Largest Contour: ",
    // Toast.LENGTH_LONG).show();

    return imgSource;
  }
Пример #3
0
  /**
   * Locate ellipses within an image
   *
   * @param grayImage Grayscale image
   * @return Ellipse locations
   */
  public EllipseLocationResult locateEllipses(Mat grayImage) {
    Mat gray = grayImage.clone();

    Filter.downsample(gray, 2);
    Filter.upsample(gray, 2);

    Imgproc.Canny(gray, gray, 5, 75, 3, true);
    Filter.dilate(gray, 2);

    Mat cacheHierarchy = new Mat();

    List<MatOfPoint> contoursTemp = new ArrayList<>();
    // Find contours - the parameters here are very important to compression and retention
    Imgproc.findContours(
        gray, contoursTemp, cacheHierarchy, Imgproc.CV_RETR_TREE, Imgproc.CHAIN_APPROX_TC89_KCOS);

    // List contours
    List<Contour> contours = new ArrayList<>();
    for (MatOfPoint co : contoursTemp) {
      contours.add(new Contour(co));
    }

    // Find ellipses by finding fit
    List<Ellipse> ellipses = new ArrayList<>();
    for (MatOfPoint co : contoursTemp) {
      contours.add(new Contour(co));
      // Contour must have at least 6 points for fitEllipse
      if (co.toArray().length < 6) continue;
      // Copy MatOfPoint to MatOfPoint2f
      MatOfPoint2f matOfPoint2f = new MatOfPoint2f(co.toArray());
      // Fit an ellipse to the current contour
      Ellipse ellipse = new Ellipse(Imgproc.fitEllipse(matOfPoint2f));

      // Draw ellipse
      ellipses.add(ellipse);
    }

    return new EllipseLocationResult(contours, ellipses);
  }
Пример #4
0
  public void run() {
    ArrayList<Geometry.Quad> squares;

    Mat image = new Mat();
    Utils.bitmapToMat(source, image);

    Mat bwimage = new Mat();
    cvtColor(image, bwimage, COLOR_RGB2GRAY);

    Mat blurred = new Mat();
    medianBlur(image, blurred, 9);

    int width = blurred.width();
    int height = blurred.height();
    int depth = blurred.depth();

    Mat gray0 = new Mat(width, height, depth);
    blurred.copyTo(gray0);

    squares = new ArrayList<Geometry.Quad>();

    // find squares in every color plane of the image
    for (int c = 0; c < 3; c++) {
      Core.mixChannels(
          Arrays.asList(blurred), Arrays.asList(new Mat[] {gray0}), new MatOfInt(c, 0));

      // try several threshold levels
      int thresholdLevel = 8;
      for (int l = 0; l < thresholdLevel; l++) {
        // use canny instead of 0 threshold level
        // canny helps catch squares with gradient shading
        Mat gray = new Mat();

        if (l == 0) {
          Canny(gray0, gray, 10.0, 20.0, 3, false);
          Mat kernel = new Mat(11, 11, CvType.CV_8UC1, new Scalar(1));
          dilate(gray, gray, kernel);
        } else {
          Mat thresh = new Mat(gray0.rows(), gray0.cols(), gray0.type());
          threshold(gray0, thresh, ((double) l) / thresholdLevel * 255, 128, THRESH_BINARY_INV);
          cvtColor(thresh, gray, COLOR_BGR2GRAY);
        }

        // find contours and store them in a list
        List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
        findContours(gray, contours, new Mat(), RETR_LIST, CHAIN_APPROX_SIMPLE);

        // test contours
        for (MatOfPoint contour : contours) {
          // approximate contour with accuracy proportional to the contour perimeter
          MatOfPoint2f thisContour = new MatOfPoint2f(contour.toArray());
          double arclength = 0.02 * arcLength(thisContour, true);
          MatOfPoint2f approx = new MatOfPoint2f();
          approxPolyDP(thisContour, approx, arclength, true);

          double area = contourArea(approx);
          boolean isConvex = isContourConvex(new MatOfPoint(approx.toArray()));

          if (approx.rows() == 4 && Math.abs(area) > SQUARE_SIZE && isConvex) {
            double maxCosine = 0;

            Point[] approxArray = approx.toArray();
            for (int j = 2; j < 5; j++) {
              double cosine =
                  Math.abs(angle(approxArray[j % 4], approxArray[j - 2], approxArray[j - 1]));
              maxCosine = Math.max(maxCosine, cosine);
            }

            if (maxCosine > THRESHOLD_COS) {
              squares.add(new Geometry.Quad(approxArray));
              Log.d(TAG, "area = " + area);
            }
          }
        }
      }
    }

    result = new Bundle();
    result.putParcelableArrayList("squares", squares);
    Log.d(TAG, "result created");

    finish();
  }
Пример #5
0
  public static void getSquare(Mat imgSource) {
    Mat sourceImage = imgSource.clone();
    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);

    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 = getCorners(p1, p2, p3, p4);
    for (Point p : source) {
      // System.out.println(p);
    }
    Mat startM = Converters.vector_Point2f_to_Mat(source);
    // Imgproc.cvtColor(sourceImage, sourceImage, Imgproc.COLOR_BGR2GRAY);
    Mat result = warp(sourceImage, startM, 5);
    // result = warp(result,result,1);
    // Imgproc.cvtColor(result, result, Imgproc.COLOR_BGR2GRAY);
    Highgui.imwrite(output, result);
    // System.out.println("Done");
    // return result;
  }