private void displayMarkerImage(Mat srcImgMat, Mat destImageMat) {
   // find location of image segment to be replaced in the destination image.
   Rect rect = calculateImageSegmentArea(destImageMat);
   Mat destSubmat = destImageMat.submat(rect.y, rect.y + rect.height, rect.x, rect.x + rect.width);
   // copy image.
   srcImgMat.copyTo(destSubmat);
 }
  /**
   * Process the given Mat, finding, classifying and displaying all resistors present.
   *
   * @param originalImg The image to parse
   */
  private void parseImage(Mat originalImg) {
    Mat workingCopy = new Mat();
    originalImg.copyTo(workingCopy);

    // blur the original image to form resistor blobs. should remove white/silver/grey bands which
    // would otherwise
    // get picked up as part of the background, leads or shadows.
    Mat blurred = new Mat();
    // Imgproc.medianBlur(workingCopy, blurred, 29);
    Imgproc.blur(workingCopy, blurred, new Size(20, 20)); // faster

    // get a mask off the background
    Mat resistorMask = new Mat();
    generateResistorMask(blurred, Imgproc.THRESH_BINARY).copyTo(resistorMask);

    // find countours in mask
    List<MatOfPoint> contours = getContours(resistorMask, originalImg, true);

    // extract resistors in input image
    List<Resistor> resistors = extractResistorsFromContours(contours, originalImg, true);

    // segment and extract colour bands for each resistor
    extractColourBandsAndClassify(resistors, true);

    // calculate and display resistance value for each resistor based on classified colour bands
    calculateAndDisplayResistanceValues(resistors);
  }
Beispiel #3
0
 public static void cvt_YUVtoGRAY(Mat src, Mat dst) {
   /** convert YUV image to RGB then GRAY colorspace */
   mSrc = new Mat();
   src.copyTo(mSrc);
   Imgproc.cvtColor(mSrc, dst, Imgproc.COLOR_YUV420sp2RGB);
   Imgproc.cvtColor(dst, dst, Imgproc.COLOR_RGB2GRAY);
 }
  public Mat onCameraFrame(Mat inputFrame) {
    inputFrame.copyTo(mRgba);
    Point center = new Point(mRgba.width() / 2, mRgba.height() / 2);
    double angle = -90;
    double scale = 1.0;

    Mat mapMatrix = Imgproc.getRotationMatrix2D(center, angle, scale);
    Imgproc.warpAffine(mRgba, mGrayMat, mapMatrix, mRgba.size(), Imgproc.INTER_LINEAR);
    return mGrayMat;
  }
 private void copyThresholdedImageToRgbImgMat(Mat thresholdedImgMat, Mat dest) {
   // convert thresholded image segment to RGB.
   Mat smallRegionImg = new Mat();
   Imgproc.cvtColor(thresholdedImgMat, smallRegionImg, Imgproc.COLOR_GRAY2BGRA, 4);
   // find location of image segment to be replaced in the destination image.
   Rect rect = calculateImageSegmentArea(dest);
   Mat destSubmat = dest.submat(rect.y, rect.y + rect.height, rect.x, rect.x + rect.width);
   // copy image.
   smallRegionImg.copyTo(destSubmat);
   smallRegionImg.release();
 }
  /**
   * Creates Resistor objects for all resistors extracted from given contours. Optionally, also
   * displays a bounding rectangle for all contours in the top left frame of the GUI.
   *
   * @param contours The contours defining the resistors
   * @param image The image from which the contours were extracted
   * @param showBoundingRect If true draws a bounding rectange for each contour
   * @return A list of Resistor objects
   */
  private List<Resistor> extractResistorsFromContours(
      List<MatOfPoint> contours, Mat image, boolean showBoundingRect) {
    List<Mat> extractedResistors = new ArrayList<Mat>();
    List<Rect> boundingRect = new ArrayList<Rect>();
    List<Resistor> resistors = new ArrayList<Resistor>();

    for (int i = 0; i < contours.size(); i++) {
      // bounding rectangle
      boundingRect.add(Imgproc.boundingRect(contours.get(i)));
      Mat mask = Mat.zeros(image.size(), CvType.CV_8U);
      Imgproc.drawContours(mask, contours, i, new Scalar(255), Core.FILLED);

      Mat contourRegion;
      Mat imageROI = new Mat();
      image.copyTo(imageROI, mask);
      contourRegion = new Mat(imageROI, boundingRect.get(i));
      extractedResistors.add(contourRegion);

      // the center of the resistor as a point within the original captured image
      Point resistorCenterPoint = findCenter(contours.get(i));

      // create a new resistor entry
      Resistor r = new Resistor(resistorCenterPoint, contourRegion);
      resistors.add(r);
    }

    if (showBoundingRect) {
      Mat drawing = new Mat();
      image.copyTo(drawing);
      for (int i = 0; i < contours.size(); i++) {
        Core.rectangle(
            drawing, boundingRect.get(i).tl(), boundingRect.get(i).br(), new Scalar(0, 0, 255), 2);
      }
      paintTL(drawing);
    }

    return resistors;
  }
  public Mat onCameraFrame(CvCameraViewFrame inputFrame) {

    mRgba = inputFrame.rgba();

    mGray = inputFrame.gray();

    if (!detectionInProgress) {
      Mat image = new Mat(mGray.rows(), mGray.cols(), mGray.type());
      mGray.copyTo(image);
      detectFaceOnFrame(image);
    }

    return mRgba;
  }
  private ArrayList<Double> applyThresholdOnImage(Mat srcImgMat, Mat outputImgMat) {
    double localThreshold;
    int startRow;
    int endRow;
    int startCol;
    int endCol;

    ArrayList<Double> localThresholds = new ArrayList<Double>();

    int numberOfTiles = mPreference.getNumberOfTiles();
    int tileWidth = (int) srcImgMat.size().height / numberOfTiles;
    int tileHeight = (int) srcImgMat.size().width / numberOfTiles;

    // Split image into tiles and apply threshold on each image tile separately.

    // process image tiles other than the last one.
    for (int tileRowCount = 0; tileRowCount < numberOfTiles; tileRowCount++) {
      startRow = tileRowCount * tileWidth;
      if (tileRowCount < numberOfTiles - 1) endRow = (tileRowCount + 1) * tileWidth;
      else endRow = (int) srcImgMat.size().height;

      for (int tileColCount = 0; tileColCount < numberOfTiles; tileColCount++) {
        startCol = tileColCount * tileHeight;
        if (tileColCount < numberOfTiles - 1) endCol = (tileColCount + 1) * tileHeight;
        else endCol = (int) srcImgMat.size().width;

        Mat tileThreshold = new Mat();
        Mat tileMat = srcImgMat.submat(startRow, endRow, startCol, endCol);
        // localThreshold = Imgproc.threshold(tileMat, tileThreshold, 0, 255, Imgproc.THRESH_BINARY
        // | Imgproc.THRESH_OTSU);
        // RNM: Adaptive threshold rules!
        localThreshold = 0x80;
        Imgproc.adaptiveThreshold(
            tileMat,
            tileThreshold,
            255,
            Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C,
            Imgproc.THRESH_BINARY,
            91,
            2);
        Mat copyMat = outputImgMat.submat(startRow, endRow, startCol, endCol);
        tileThreshold.copyTo(copyMat);
        tileThreshold.release();
        localThresholds.add(localThreshold);
      }
    }

    return localThresholds;
  }
  /* (non-Javadoc)
   * @see java.lang.Runnable#run()
   */
  @Override
  public void run() {
    if (MODE.equals("VIDEO")) {
      Mat capturedImage = new Mat();
      VideoCapture vc = new VideoCapture(DEVICE);
      if (!vc.isOpened()) {
        System.out.println("Capture Failed!");
        return;
      }
      System.out.println("Device " + DEVICE + " opened");
      // set captured resolution
      vc.set(Highgui.CV_CAP_PROP_FRAME_WIDTH, 640);
      vc.set(Highgui.CV_CAP_PROP_FRAME_HEIGHT, 480);

      // Manually set exposure
      vc.set(15, -11);
      while (true) {
        vc.read(capturedImage);
        if (capturedImage != null) {
          // flip the image to compensate for camera orientation
          Core.flip(capturedImage, capturedImage, -1);
          capturedImage.copyTo(finalDisplayImg);
          parseImage(capturedImage);
        }
      }
    } else { // STILL IMAGE
      Mat capturedImage = Highgui.imread(IMAGE_FILEPATH);
      while (true) {
        if (needUpdate) {
          capturedImage.copyTo(finalDisplayImg);
          parseImage(capturedImage);
          needUpdate = false;
        }
      }
    }
  }
Beispiel #10
0
 @Override
 public Result process(CvPipeline pipeline) throws Exception {
   Mat mat = pipeline.getWorkingImage();
   Mat mask = mat.clone();
   Mat masked = mat.clone();
   Scalar color = FluentCv.colorToScalar(Color.black);
   mask.setTo(color);
   masked.setTo(color);
   Core.inRange(
       mat,
       new Scalar(hueMin, saturationMin, valueMin),
       new Scalar(hueMax, saturationMax, valueMax),
       mask);
   Core.bitwise_not(mask, mask);
   mat.copyTo(masked, mask);
   return new Result(masked);
 }
  public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
    mRgba = inputFrame.rgba();

    if (mIsColorSelected) {
      abc = mDetector.process(mRgba);
      // hehe.setText(abc.toString());
      List<MatOfPoint> contours = mDetector.getContours();
      Log.e(TAG, "Contours count: " + contours.size());
      Imgproc.drawContours(mRgba, contours, -1, CONTOUR_COLOR);

      Mat colorLabel = mRgba.submat(4, 68, 4, 68);
      colorLabel.setTo(mBlobColorRgba);

      Mat spectrumLabel = mRgba.submat(4, 4 + mSpectrum.rows(), 70, 70 + mSpectrum.cols());
      mSpectrum.copyTo(spectrumLabel);
    }

    return mRgba;
  }
  public static Mat Histogram(Mat im) {

    Mat img = im;

    Mat equ = new Mat();
    img.copyTo(equ);
    // Imgproc.blur(equ, equ, new Size(3, 3));

    Imgproc.cvtColor(equ, equ, Imgproc.COLOR_BGR2YCrCb);
    List<Mat> channels = new ArrayList<Mat>();
    Core.split(equ, channels);
    Imgproc.equalizeHist(channels.get(0), channels.get(0));
    Core.merge(channels, equ);
    Imgproc.cvtColor(equ, equ, Imgproc.COLOR_YCrCb2BGR);

    Mat gray = new Mat();
    Imgproc.cvtColor(equ, gray, Imgproc.COLOR_BGR2GRAY);
    Mat grayOrig = new Mat();
    Imgproc.cvtColor(img, grayOrig, Imgproc.COLOR_BGR2GRAY);
    System.out.println("Histogram work ///");
    return grayOrig;
  }
  /**
   * @param inputImg
   * @param minValue
   * @param maxValue
   * @return Mat
   */
  public static Mat thresholding(Mat inputImg, Integer minValue, Integer maxValue) {

    Mat frame = inputImg;
    // яскравість
    // frame.convertTo(frame , -1, 10d * 33 / 100, 0);
    // Imgproc.medianBlur(frame,frame, 17);

    // Core.bitwise_not(frame,frame );

    // Mat frame = new Mat(image.rows(), image.cols(), image.type());

    // frame.convertTo(frame, -1, 10d * 20 / 100, 0);

    Mat hsvImg = new Mat();
    List<Mat> hsvPlanes = new ArrayList<>();
    Mat thresholdImg = new Mat();

    int thresh_type = Imgproc.THRESH_BINARY_INV;

    // if (this.inverse.isSelected())
    // thresh_type = Imgproc.THRESH_BINARY;

    // threshold the image with the average hue value
    // System.out.println("size " +frame.size());
    hsvImg.create(frame.size(), CvType.CV_8U);
    // Imgproc.cvtColor(frame, hsvImg, Imgproc.COLOR_BGR2HSV);
    Core.split(hsvImg, hsvPlanes);

    // get the average hue value of the image
    // double threshValue = PreProcessingOperation.getHistAverage(hsvImg, hsvPlanes.get(0));
    // System.out.println(threshValue);
    /*
    if(threshValue > 40){
        maxValue = 160;
    }else{
        maxValue = 40;
    }*/

    //        Imgproc.threshold(hsvPlanes.get(1), thresholdImg, minValue , maxValue , thresh_type);

    Imgproc.blur(thresholdImg, thresholdImg, new Size(27, 27));

    // dilate to fill gaps, erode to smooth edges
    Imgproc.dilate(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
    Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);

    Imgproc.threshold(thresholdImg, thresholdImg, minValue, maxValue, Imgproc.THRESH_BINARY);

    // create the new image
    Mat foreground = new Mat(frame.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
    Core.bitwise_not(thresholdImg, foreground);

    frame.copyTo(foreground, thresholdImg);

    ///////////////////////////////////////////////////////////////////////////////////////
    ///
    ////

    return foreground;
    /*Mat hsvImg = new Mat();
    List<Mat> hsvPlanes = new ArrayList<>();
    Mat thresholdImg = new Mat();
    int thresh_type = Imgproc.THRESH_BINARY_INV;
    // threshold the image with the average hue value
    hsvImg.create(inputImg.size(), CvType.CV_8U);
    Imgproc.cvtColor(inputImg, hsvImg, Imgproc.COLOR_BGR2HSV);
    Core.split(hsvImg, hsvPlanes);
    // get the average hue value of the image
    double threshValue = PreProcessingOperation.getHistAverage(hsvImg, hsvPlanes.get(0));
    Imgproc.threshold(hsvPlanes.get(0), thresholdImg, minValue,
            maxValue, thresh_type);
    Imgproc.blur(thresholdImg, thresholdImg, new Size(3, 3));
    // dilate to fill gaps, erode to smooth edges
    Imgproc.dilate(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 3);
    Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
    Imgproc.threshold(thresholdImg, thresholdImg, minValue,
            maxValue, Imgproc.THRESH_BINARY);
    // create the new image
    Mat foreground = new Mat(inputImg.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
    inputImg.copyTo(foreground, thresholdImg);
    Core.bitwise_not(foreground,foreground);
    return foreground;*/
  }
  /**
   * @param inputImg
   * @return Mat
   */
  public static Mat kmeans(Mat inputImg) {

    Mat rgba = inputImg;
    Mat tempMat = inputImg;
    rgba = new Mat(inputImg.cols(), inputImg.rows(), CvType.CV_8UC3);
    inputImg.copyTo(rgba);

    List<Mat> hsv_planes_temp = new ArrayList<Mat>(3);
    Core.split(tempMat, hsv_planes_temp);

    double threshValue1 = PreProcessingOperation.getHistAverage(inputImg, hsv_planes_temp.get(0));
    sample.util.Estimate.setFirstHistAverageValue(threshValue1);
    System.out.println("Defore eqau " + threshValue1);

    System.out.println(
        Estimate.getBlueAverage() + " ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;");

    if (threshValue1 > 140) {
      if (Estimate.getBlueAverage() > 110) {
        rgba.convertTo(rgba, -1, 10d * 31 / 100, 0);
        System.out.println("11");
      } else {
        rgba.convertTo(rgba, -1, 10d * 40 / 100, 0);
        System.out.println("12");
      }
    } else if (threshValue1 > 135) {
      rgba.convertTo(rgba, -1, 10d * 32 / 100, 0);
      System.out.println("21");
    } else if (threshValue1 > 125) {
      if (Estimate.getBlueAverage() > 110) {
        rgba.convertTo(rgba, -1, 10d * 30 / 100, 0);
        rgba = PreProcessing.Dilate(rgba, 5);
        System.out.println("31");
      } else {
        rgba.convertTo(rgba, -1, 10d * 37 / 100, 0);
        System.out.println("32");
      }
    } else if (threshValue1 > 120) {
      rgba.convertTo(rgba, -1, 10d * 35 / 100, 0);
      System.out.println("41");
    } else if (threshValue1 > 110) {
      if (Estimate.getBlueAverage() > 110) {
        rgba.convertTo(rgba, -1, 10d * 35 / 100, 0);
        rgba = PreProcessing.Dilate(rgba, 5);
        System.out.println("51");
      }
    } else if (threshValue1 > 100) {
      if (Estimate.getBlueAverage() > 107) {
        rgba.convertTo(rgba, -1, 10d * 24 / 100, 0);
        rgba = PreProcessing.Dilate(rgba, 5);
        System.out.println("61");
      } else if (Estimate.getBlueAverage() > 90) {
        rgba.convertTo(rgba, -1, 10d * 30 / 100, 0);
        rgba = PreProcessing.Dilate(rgba, 5);
        System.out.println("62");
      }
    } else if (threshValue1 > 50) {

      if (Estimate.getBlueAverage() > 160) {
        rgba.convertTo(rgba, -1, 10d * 30 / 100, 0);
        rgba = PreProcessing.Dilate(rgba, 3);
        System.out.println("81");
      } else if (Estimate.getBlueAverage() > 160) {
        rgba.convertTo(rgba, -1, 10d * 27 / 100, 0);
        rgba = PreProcessing.Dilate(rgba, 9);
        System.out.println("82");
      } else if (Estimate.getBlueAverage() > 130) {
        rgba.convertTo(rgba, -1, 10d * 30 / 100, 0);
        rgba = PreProcessing.Dilate(rgba, 9);
        System.out.println("83");
      } else if (Estimate.getBlueAverage() > 70) {
        rgba.convertTo(rgba, -1, 10d * 29 / 100, 0);
        rgba = PreProcessing.Dilate(rgba, 9);
        System.out.println("84");
      }
    } else if (threshValue1 > 30) {
      if (Estimate.getBlueAverage() > 190) {
        rgba.convertTo(rgba, -1, 10d * 25 / 100, 0);
        System.out.println("91");
      } else if (Estimate.getBlueAverage() > 160) {
        rgba.convertTo(rgba, -1, 10d * 35 / 100, 0);
        System.out.println("92");
      }
    } else {
      if (Estimate.getBlueAverage() > 240) {
        rgba.convertTo(rgba, -1, 10d * 24 / 100, 0);
        System.out.println("7");
      } else {
        rgba.convertTo(rgba, -1, 10d * 17 / 100, 0);
        System.out.println("7");
      }
    }
    tempMat.release();

    Mat mHSV = new Mat();
    Imgproc.cvtColor(rgba, mHSV, Imgproc.COLOR_RGBA2RGB, 3);
    Imgproc.cvtColor(rgba, mHSV, Imgproc.COLOR_RGB2HSV, 3);
    List<Mat> hsv_planes = new ArrayList<Mat>(3);
    Core.split(mHSV, hsv_planes);

    Mat channel = hsv_planes.get(0);
    channel = Mat.zeros(mHSV.rows(), mHSV.cols(), CvType.CV_8UC1);
    hsv_planes.set(2, channel);
    Core.merge(hsv_planes, mHSV);

    mHSV.convertTo(mHSV, CvType.CV_8UC1);
    mHSV = Histogram(mHSV);

    /*
    Mat clusteredHSV = new Mat();
    mHSV.convertTo(mHSV, CvType.CV_32FC3);
    TermCriteria criteria = new TermCriteria(TermCriteria.EPS + TermCriteria.MAX_ITER,100,0.1);
    Core.kmeans(mHSV, 1, clusteredHSV, criteria, 20, Core.KMEANS_PP_CENTERS);
    Mat hsvImg = new Mat();
    List<Mat> hsvPlanes = new ArrayList<>();
    Mat thresholdImg = new Mat();
    int thresh_type = Imgproc.THRESH_BINARY_INV;
    hsvImg.create(mHSV.size(), CvType.CV_8U);
    Imgproc.cvtColor(mHSV, hsvImg, Imgproc.COLOR_BGR2HSV);
    Core.split(hsvImg, hsvPlanes);
    Imgproc.threshold(hsvPlanes.get(1), thresholdImg, 0 , 200 , thresh_type);
    double threshValue = PreProcessingOperation.getHistAverage(hsvImg, hsvPlanes.get(0));
    Estimate.setSecondHistAverageValue(threshValue);
    System.out.println("After equa " + Estimate.getSecondHistAverageValue());*/

    Imgproc.threshold(mHSV, mHSV, 0, 150, Imgproc.THRESH_BINARY_INV);
    // mHSV.convertTo(mHSV, CvType.CV_8UC1);
    return mHSV;
  }
  /**
   * Extracts and classifies colour bands for each Resistor. Each ColourBand object is instantiated
   * and linked to their parent Resistor object.
   *
   * @param resistorList A list of Resistor objects from which to extract the colour bands
   * @param paintDebugInfo If ture, the extracted colour band ROIs are displayed on the GUI
   */
  private void extractColourBandsAndClassify(List<Resistor> resistorList, boolean paintDebugInfo) {
    if (resistorList.size() > 0) {
      for (int r = 0; r < resistorList.size(); r++) {
        Mat resImg = resistorList.get(r).resistorMat;

        Mat imgHSV = new Mat();
        Mat satImg = new Mat();
        Mat hueImg = new Mat();

        // convert to HSV
        Imgproc.cvtColor(resImg, imgHSV, Imgproc.COLOR_BGR2HSV);
        ArrayList<Mat> channels = new ArrayList<Mat>();
        Core.split(imgHSV, channels);
        // extract channels
        satImg = channels.get(1); // saturation
        hueImg = channels.get(0); // hue

        // threshold saturation channel
        Mat threshedROISatBands = new Mat(); // ~130 sat thresh val
        Imgproc.threshold(satImg, threshedROISatBands, SAT_BAND_THRESH, 255, Imgproc.THRESH_BINARY);

        // threshold hue channel
        Mat threshedROIHueBands = new Mat(); // ~50 hue thresh val
        Imgproc.threshold(hueImg, threshedROIHueBands, HUE_BAND_THRESH, 255, Imgproc.THRESH_BINARY);

        // combine the thresholded binary images
        Mat bandROI = new Mat();
        Core.bitwise_or(threshedROIHueBands, threshedROISatBands, bandROI);

        // find contours in binary ROI image
        ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
        Mat hierarchy = new Mat();
        Imgproc.findContours(
            bandROI,
            contours,
            hierarchy,
            Imgproc.RETR_EXTERNAL,
            Imgproc.CHAIN_APPROX_SIMPLE,
            new Point(0, 0));

        // remove any remaining noise by only keeping contours which area > threshold
        for (int i = 0; i < contours.size(); i++) {
          double area = Imgproc.contourArea(contours.get(i));
          if (area < MIN_BAND_AREA) {
            contours.remove(i);
            i--;
          }
        }

        // create a ColourBand object for each detected band
        // storing its center, the contour and the bandROI
        for (int i = 0; i < contours.size(); i++) {
          MatOfPoint contour = contours.get(i);

          // extract this colour band and store in a Mat
          Rect boundingRect = Imgproc.boundingRect(contour);
          Mat mask = Mat.zeros(bandROI.size(), CvType.CV_8U);
          Imgproc.drawContours(mask, contours, i, new Scalar(255), Core.FILLED);
          Mat imageROI = new Mat();
          resImg.copyTo(imageROI, mask);
          Mat colourBandROI = new Mat(imageROI, boundingRect);

          // instantiate new ColourBand object
          ColourBand cb = new ColourBand(findCenter(contour), contour, colourBandROI);

          // cluster the band colour
          cb.clusterBandColour(BAND_COLOUR_K_MEANS);

          // classify using the Lab colourspace as feature vector
          Mat sampleMat =
              new Mat(1, 3, CvType.CV_32FC1); // create a Mat contacting the clustered band colour
          sampleMat.put(0, 0, cb.clusteredColourLAB[0]);
          sampleMat.put(0, 1, cb.clusteredColourLAB[1]);
          sampleMat.put(0, 2, cb.clusteredColourLAB[2]);
          Mat classifiedValue = new Mat(1, 1, CvType.CV_32FC1);
          Mat neighborResponses = new Mat(); // dont actually use this
          Mat dists = new Mat(); // dont actually use this
          // classify
          knn.find_nearest(sampleMat, 3, classifiedValue, neighborResponses, dists);

          // cast classified value into Colour enum and store
          cb.classifiedColour = ColourEnumVals[(int) classifiedValue.get(0, 0)[0]];
          // add the band to the parent resistor
          resistorList.get(r).bands.add(cb);
        }

        // paint the extracted band ROIs
        if (paintDebugInfo) {
          Mat finalBandROIMask = Mat.zeros(bandROI.size(), CvType.CV_8U);
          for (int i = 0; i < contours.size(); i++) {
            Scalar color = new Scalar(255, 255, 255);
            Imgproc.drawContours(
                finalBandROIMask, contours, i, color, -1, 4, hierarchy, 0, new Point());
          }
          Mat colourROI = new Mat();
          resImg.copyTo(colourROI, finalBandROIMask);
          paintResistorSubRegion(colourROI, r);
        }
      }
    }
  }
Beispiel #16
0
  public static void Circle(List<MatOfPoint> contours, int index) {
    int i = index;
    Mat mRGBA = new Mat();
    Utils.bitmapToMat(image, mRGBA);
    // cyklus s podmienkou na konci
    do {
      int buff[] = new int[4];
      hierarchy.get(0, i, buff);

      // Get contour form list
      Mat contour = contours.get(i);

      // id kont�ry
      int id = i;

      // dostaneme �a��ie id kont�ry
      i = buff[0];

      // zis�ujeme �i m�me dostato�ne ve�k� kont�ru aby sme sa �ou v�bec zaoberali
      if (Imgproc.contourArea(contour) > 500) {

        List<Point> points = new ArrayList<Point>();

        // dostaneme celkov� po�et kont�r
        int num = (int) contour.total();

        // vytvor�me si pole o dvojn�sobnej ve�kosti samotnej kontury
        int temp[] = new int[num * 2];

        // na��tame si kont�ru do do�asnej premennej
        contour.get(0, 0, temp);

        // konvertujeme  List<Point> do MatOfPoint2f pre pou�itie fitEllipse
        for (int j = 0; j < num * 2; j = j + 2) {
          points.add(new Point(temp[j], temp[j + 1]));
        }
        MatOfPoint2f specialPointMtx = new MatOfPoint2f(points.toArray(new Point[0]));

        // do premennej bound uklad�me dokonal� elipsu
        RotatedRect bound = Imgproc.fitEllipse(specialPointMtx);

        // Vypo��ta sa hodnota pi
        double pi =
            Imgproc.contourArea(contour) / ((bound.size.height / 2) * (bound.size.width / 2));

        // zis�ujeme toleranciu pi - zaoplenie
        if (Math.abs(pi - 3.14) > 0.03) {
          int k = buff[2];
          // zis�ujeme �i existuje nejak� rodi� kont�ry
          if (k != -1) {
            Circle(contours, k);
          }
          continue;
        }

        // konvertujeme MatOfPoint2f do MatOfPoint  pre funckiu fitEllipse - rozdie� je len v 32-bit
        // float a 32-bit int
        MatOfPoint NewMtx = new MatOfPoint(specialPointMtx.toArray());
        // dostaneme s�radnice najmen�ieho mo�n�ho �tvorca
        Rect box = Imgproc.boundingRect(NewMtx);
        // nacita obrazok znova
        Mat mat_for_count = new Mat();
        Utils.bitmapToMat(image, mat_for_count);
        // vytvori sa klon stvorca - dobry kandidat pre vyhladanie
        Mat candidate = ((mat_for_count).submat(box)).clone();
        // napln maticu binarnou ciernou
        Mat mask = new Mat(box.size(), candidate.type(), new Scalar(0, 0, 0));
        // naplni ciernu plochu bielimi konturami
        Imgproc.drawContours(
            mask,
            contours,
            id,
            new Scalar(255, 255, 255),
            -1,
            8,
            hierarchy,
            0,
            new Point(-box.x, -box.y));
        // ulozi sa kandidat
        Mat roi = new Mat(candidate.size(), candidate.type(), new Scalar(255, 255, 255));
        // ulozia sa len informacie o kandidatovi
        candidate.copyTo(roi, mask);

        double longAxis;
        double shortAxis;
        // ziska dve osy elipsy
        if (bound.size.height < bound.size.width) {
          shortAxis = bound.size.height / 2;
          longAxis = bound.size.width / 2;
        } else {
          shortAxis = bound.size.width / 2;
          longAxis = bound.size.height / 2;
        }

        // zastavi sa vyhladavanie pokial je elipsa prilis ovalna
        if ((longAxis / shortAxis) < 2.0) {
          signList.add(roi);
          boxList.add(box);
        }
      }
      // zis�uje sa �i je tam e�te �al�� kandid�t
    } while (i != -1);
  }
Beispiel #17
0
  public void processWithContours(Mat in, Mat out) {
    int playSquares = 32; // number of playable game board squares

    // keep track of starting row square
    int parity = 0; // 0 is even, 1 is odd, tied to row number
    int count = 0; // row square
    int rowNum = 0; // row number, starting at 0

    int vsegment = in.rows() / 8; // only accounts 8 playable
    int hsegment = in.cols() / 10; // 8 playable, 2 capture
    int hOffset = hsegment * 2; // offset for playable board
    int vOffset = vsegment + 40;

    // For angle of camera
    int dx = 80;
    int ddx = 0;
    hsegment -= 16;

    int dy = 20;
    vsegment -= 24;
    int ddy = 0;

    // Go through all playable squares
    for (int i = 0; i < playSquares; i++) {
      // change offset depending on the row
      if (parity == 0) // playable squares start on 2nd square from left
      {
        if (rowNum >= 5) dx -= 3;
        hOffset = hsegment * 2 + dx;
      } else // playable squares start on immediate left
      {
        if (rowNum >= 5) dx -= 3;
        hOffset = hsegment + dx;
      }

      if (rowNum == 0) ddy = 5;
      if (rowNum == 4) if (count == 6) ddx = 10;
      if (rowNum == 5) {
        if (count == 0) ddx = -6;
        else if (count == 2) ddx = 6;
        else if (count == 4) ddx = 12;
        else if (count == 6) ddx = 20;
      }
      if (rowNum == 6) {
        if (count == 0) ddx = 0;
        else if (count == 2) ddx = 16;
        else if (count == 4) ddx = 32;
        else if (count == 6) ddx = 40;
      }
      if (rowNum == 7) {
        if (count == 0) ddx = 6;
        else if (count == 2) ddx = 24;
        else if (count == 4) ddx = 40;
        else ddx = 52;
      }

      // find where roi should be
      // System.out.println("" + vOffset);
      Point p1 =
          new Point(
              hOffset + count * hsegment + ddx + 5,
              vOffset + rowNum * vsegment - dy - 5 - ddy); // top left point of rectangle (x,y)
      Point p2 =
          new Point(
              hOffset + (count + 1) * hsegment + ddx - 5,
              vOffset
                  + (rowNum + 1) * vsegment
                  - dy
                  - 5
                  - ddy); // bottom right point of rectangle (x,y)

      // create rectangle that is board square
      Rect bound = new Rect(p1, p2);

      Mat roi;
      char color;
      if (i == 0) {
        // frame only includes rectangle
        roi = new Mat(in, bound);

        // get the color
        color = identifyColor(roi);

        // copy input image to output image
        in.copyTo(out);
      } else {
        // frame only includes rectangle
        roi = new Mat(out, bound);

        // get the color
        color = identifyColor(roi);
      }

      Imgproc.cvtColor(roi, roi, Imgproc.COLOR_BGR2GRAY); // change to single color

      Mat canny = new Mat();
      Imgproc.Canny(roi, canny, 20, 40); // make image a canny image that is only edges; 2,4
      // lower threshold values find more edges
      List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
      Mat hierarchy = new Mat(); // holds nested contour information
      Imgproc.findContours(
          canny,
          contours,
          hierarchy,
          Imgproc.RETR_LIST,
          Imgproc.CHAIN_APPROX_SIMPLE); // Imgproc.RETR_LIST, TREE

      System.out.println(++test + "\t" + contours.size());

      if (contours.size() > 3) // or error value for color is below 1
      {
        switch (color) {
          case COLOR_BLUE:
            // Imgproc.rectangle(out, p1, p2, new Scalar(255, 0, 0), 2);
            Core.rectangle(out, p1, p2, new Scalar(255, 0, 0), 2);
            board[i] = CheckersBoard.BLACK; // end user's piece
            break;
          case COLOR_ORANGE:
            // Imgproc.rectangle(out, p1, p2, new Scalar(0, 128, 255), 2);
            Core.rectangle(out, p1, p2, new Scalar(0, 128, 255), 2);
            board[i] = CheckersBoard.WHITE; // system's piece
            break;
          case COLOR_WHITE:
            // Imgproc.rectangle(out, p1, p2, new Scalar(255, 255, 255), 2);
            Core.rectangle(out, p1, p2, new Scalar(255, 255, 255), 2);
            board[i] = CheckersBoard.EMPTY;
            break;
          case COLOR_BLACK: // this is black
            // Imgproc.rectangle(out, p1, p2, new Scalar(0, 0, 0), 2);
            Core.rectangle(
                out,
                p1,
                p2,
                new Scalar(0, 0, 0),
                2); // maybe add 8, 0 as line type and fractional bits
            board[i] = CheckersBoard.EMPTY;
            break;
        }
      }

      System.out.println("in color switch " + board[i]);
      count += 2;
      if (count == 8) {
        parity = ++parity % 2; // change odd or even
        count = 0;
        rowNum++;
        hsegment += 2;
        dx -= 10;
        dy += 10;
        vsegment += 3;
        ddy = 0;
      }
    }
  }
Beispiel #18
0
  /**
   * Determines which pieces are kings
   *
   * @param in Mat image of board
   */
  public void determineKings(Mat in) {
    int playSquares = 32;

    Mat dst = new Mat(in.rows(), in.cols(), in.type());
    in.copyTo(dst);

    Imgproc.cvtColor(dst, dst, Imgproc.COLOR_BGR2GRAY); // change to single color

    Mat canny = new Mat();
    Imgproc.Canny(dst, canny, 100, 200); // make image a canny image that is only edges; 2,4
    // lower threshold values find more edges
    List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
    Mat hierarchy = new Mat(); // holds nested contour information
    Imgproc.findContours(
        canny,
        contours,
        hierarchy,
        Imgproc.RETR_LIST,
        Imgproc.CHAIN_APPROX_SIMPLE); // Imgproc.RETR_LIST, TREE

    // draw contour image
    Mat mask = new Mat();
    mask = Mat.zeros(dst.size(), dst.type());
    Imgproc.drawContours(
        mask, contours, -1, new Scalar(255, 255, 255), 1, 8, hierarchy, 2, new Point());
    Highgui.imwrite("contours.jpg", mask);

    ArrayList occupied = new ArrayList<Integer>();
    for (int i = 0; i < playSquares; i++) {
      if (board[i] != 0) occupied.add(i);
    }

    for (int i = 0; i < contours.size(); i++) // assuming only contours are checker pieces
    {
      // determine if it should be a king
      // use Rect r = Imgproc.boundingRect then find height of it by r.height

      // Get bounding rect of contour
      Rect bound = Imgproc.boundingRect(contours.get(i));

      if (bound.height > in.rows() / 8) {
        // board[(int) occupied.get(0)]++; // make it a king
        // occupied.remove(0);
      }
    }

    // or apply to each region of interest

    /*
    // keep track of starting row square
    int parity = 0; // 0 is even, 1 is odd, tied to row number
    int count = 0; // row square
    int rowNum = 0; // row number, starting at 0

    int vsegment = in.rows() / 8; // only accounts 8 playable
    int hsegment = in.cols() / 12; // 8 playable, 2 capture, 2 extra
    int offset = hsegment * 2; // offset for playable board

    // For angle of camera
    int dx = 48;
    hsegment -= 8;


    // Go through all playable squares
    for (int i = 0; i < playSquares; i++)
    {
    	// change offset depending on the row
    	if (parity == 0) // playable squares start on immediate left
    		offset = hsegment * 3 + dx;
    	else // playable squares start on 2nd square from left
    		offset = hsegment * 2 + dx;

    	// find where roi should be
    	Point p1 = new Point(offset + count * hsegment, rowNum * vsegment); // top left point of rectangle (x,y)
    	Point p2 = new Point(offset + (count + 1) * hsegment, (rowNum + 1) * vsegment); // bottom right point of rectangle (x,y)

    	// create rectangle that is board square
    	Rect bound = new Rect(p1, p2);

    	// frame only includes rectangle
    	Mat roi = new Mat(in, bound);

           Imgproc.cvtColor(roi, roi, Imgproc.COLOR_BGR2GRAY); // change to single color

           Mat canny = new Mat();
           Imgproc.Canny(roi, canny, 2, 4); // make image a canny image that is only edges; 2,4
           // lower threshold values find more edges
           List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
           Mat hierarchy = new Mat(); // holds nested contour information
           Imgproc.findContours(canny, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); // Imgproc.RETR_LIST, TREE

           // Get bounding rect of contour
              Rect rect = Imgproc.boundingRect(contours.get(0));

              if (rect.height > in.rows() / 8)
    	{
    		board[i]++; // make it a king
    	}

    	count += 2;
    	if (count == 8)
    	{
    		parity = ++parity % 2; // change odd or even
    		count = 0;
    		rowNum++;
    		hsegment += 1;
    		dx -= 6;
    	}
    }*/
  }
Beispiel #19
0
  /**
   * Processes the board image
   *
   * @param in image captured of board
   * @param out processed image of board
   */
  public void processFrame(Mat in, Mat out) {
    // multiple regions of interest

    int playSquares = 32; // number of playable game board squares

    // keep track of starting row square
    int parity = 0; // 0 is even, 1 is odd, tied to row number
    int count = 0; // row square
    int rowNum = 0; // row number, starting at 0

    int vsegment = in.rows() / 8; // only accounts 8 playable
    int hsegment = in.cols() / 10; // 8 playable, 2 capture
    int hOffset = hsegment * 2; // offset for playable board
    int vOffset = vsegment + 40;

    // For angle of camera
    int dx = 80;
    int ddx = 0;
    hsegment -= 16;

    int dy = 20;
    vsegment -= 24;

    // Go through all playable squares
    for (int i = 0; i < playSquares; i++) {
      // change offset depending on the row
      if (parity == 0) // playable squares start on 2nd square from left
      {
        if (rowNum >= 5) dx -= 3;
        hOffset = hsegment * 2 + dx;
      } else // playable squares start on immediate left
      {
        if (rowNum >= 5) dx -= 3;
        hOffset = hsegment + dx;
      }

      if (rowNum == 4) if (count == 6) ddx = 10;
      if (rowNum == 5) {
        if (count == 0) ddx = -6;
        else if (count == 2) ddx = 6;
        else if (count == 4) ddx = 12;
        else if (count == 6) ddx = 20;
      }
      if (rowNum == 6) {
        if (count == 0) ddx = 0;
        else if (count == 2) ddx = 16;
        else if (count == 4) ddx = 32;
        else if (count == 6) ddx = 40;
      }
      if (rowNum == 7) {
        if (count == 0) ddx = 0;
        else if (count == 2) ddx = 24;
        else if (count == 4) ddx = 40;
        else ddx = 52;
      }

      // find where roi should be
      // System.out.println("" + vOffset);
      Point p1 =
          new Point(
              hOffset + count * hsegment + ddx,
              vOffset + rowNum * vsegment - dy); // top left point of rectangle (x,y)
      Point p2 =
          new Point(
              hOffset + (count + 1) * hsegment + ddx,
              vOffset + (rowNum + 1) * vsegment - dy); // bottom right point of rectangle (x,y)

      // create rectangle that is board square
      Rect bound = new Rect(p1, p2);

      char color;
      if (i == 0) {
        // frame only includes rectangle
        Mat roi = new Mat(in, bound);

        // get the color
        color = identifyColor(roi);

        // copy input image to output image
        in.copyTo(out);
      } else {
        // frame only includes rectangle
        Mat roi = new Mat(out, bound);

        // get the color
        color = identifyColor(roi);
      }

      // annotate the output image
      // scalar values as (blue, green, red)
      switch (color) {
        case COLOR_BLUE:
          // Imgproc.rectangle(out, p1, p2, new Scalar(255, 0, 0), 2);
          Core.rectangle(out, p1, p2, new Scalar(255, 0, 0), 2);
          board[i] = CheckersBoard.BLACK; // end user's piece
          break;
        case COLOR_ORANGE:
          // Imgproc.rectangle(out, p1, p2, new Scalar(0, 128, 255), 2);
          Core.rectangle(out, p1, p2, new Scalar(0, 128, 255), 2);
          board[i] = CheckersBoard.WHITE; // system's piece
          break;
        case COLOR_WHITE:
          // Imgproc.rectangle(out, p1, p2, new Scalar(255, 255, 255), 2);
          Core.rectangle(out, p1, p2, new Scalar(255, 255, 255), 2);
          board[i] = CheckersBoard.EMPTY;
          break;
        case COLOR_BLACK: // this is black
          // Imgproc.rectangle(out, p1, p2, new Scalar(0, 0, 0), 2);
          Core.rectangle(
              out,
              p1,
              p2,
              new Scalar(0, 0, 0),
              2); // maybe add 8, 0 as line type and fractional bits
          board[i] = CheckersBoard.EMPTY;
          break;
      }

      count += 2;
      if (count == 8) {
        parity = ++parity % 2; // change odd or even
        count = 0;
        rowNum++;
        hsegment += 2;
        dx -= 10;
        dy += 10;
        vsegment += 3;
      }
    }
  }
  public void hpFind(Mat mRgba, Mat mGray, WorkingHeadPose hp, Rect[] facesArray)
        // public void hpFind(Mat mRgba,Mat mGray,HeadPose hp)
      {

    int i;
    Log.i("HeadPose", "hpFind:Total Faces Found" + facesArray.length);
    if (hp.hpstatus == HeadPoseStatus.NONE) {
      if (facesArray.length < 1) return;
      TempFace = facesArray.clone();
      hp.cornerCount = hp.maxCorners;
      Rect roi =
          new Rect(
              (int) facesArray[0].tl().x,
              (int) (facesArray[0].tl().y),
              facesArray[0].width,
              (int) (facesArray[0].height)); // imran
      Mat cropped = new Mat();
      Mat GrayClone = new Mat();
      GrayClone = mGray.clone();
      cropped = GrayClone.submat(roi);
      hpFindCorners(cropped, hp);
      // mGray is untouched
      // ******** working fine upto here

      // Map face points to model

      if (hp.cornerCount < 4) return;

      Vector<Point3> points = new Vector<Point3>();
      if (hp.corners.total()
          > 0) // adding to make sure, copying is done perfectly.imran,was getting exception
      {
        Log.i("hpFind+", "hp.corners.total()" + hp.corners.total());
        Log.i("hpFind+", "hp.cornerCount" + hp.cornerCount);

        // Point3 temp1;//=new Point3();

        for (i = 0; i < hp.cornerCount; i++) {
          if (i == hp.corners.total()) break;
          // Log.i("hpFind+","Itertion"+i);
          points.add(
              new Point3(
                  (hp.corners.toList().get(i).x / facesArray[0].width) - 0.5,
                  -(hp.corners.toList().get(i).y / facesArray[0].height) + 0.5,
                  0.5 * Math.sin(PI * (hp.corners.toList().get(i).x / facesArray[0].width))));
          // modelPoints.toList().set(i,
          // hpmodel(hp.corners.toList().get(i).x/facesArray[0].width,hp.corners.toList().get(i).x/facesArray[0].height));
          // temp1=new Point3((hp.corners.toList().get(i).x/facesArray[0].width) -
          // 0.5,-(hp.corners.toList().get(i).y/facesArray[0].height) + 0.5, 0.5 * Math.sin(PI
          // *(hp.corners.toList().get(i).x/facesArray[0].width)));
          // modelPoints. .p  .toList().set .set(i,temp1);

        }
        modelPoints.fromList(points);
      }

      // imran example from marker.java , search for Point3f

      // Traslate corners from face coordinated to image coordinates
      for (i = 0; i < hp.cornerCount; i++) {
        if (i == hp.corners.total()) break;
        hp.corners.toList().get(i).x += facesArray[0].tl().x;
        hp.corners.toList().get(i).y += facesArray[0].br().y;
        // hp.corners.toList().set(i, hp.corners.toList().get(i)+facesArray[0].tl().x);

      }
      hp.corners.copyTo(hp.tempcorners); // .clone();
      // Change status
      hp.hpstatus = HeadPoseStatus.KEYFRAME;
    } else {
      if (facesArray.length > 1)
        TempFace = facesArray.clone(); // imran assigning here also,to better measure

      MatOfPoint2f corners2f = new MatOfPoint2f();
      hp.corners.convertTo(corners2f, CvType.CV_32FC2);
      hp.previousCorners = corners2f;
      corners2f.convertTo(hp.corners, CvType.CV_32S);

      hpTrack(mRgba, hp, facesArray);
      Point center = new Point();

      if (hp.cornerCount < 4) {
        hp.hpstatus = HeadPoseStatus.NONE;
        return;
      }

      hp.hpstatus = HeadPoseStatus.TRACKING;
    }
    if (hp.previousFrame == null) // imran
    {
      // hp.previousFrame =new Mat(mRgba.width(),mRgba.height(),CvType);
      hp.previousFrame = new Mat(mRgba.size(), CvType.CV_8UC4);
    }
    mRgba.copyTo(hp.previousFrame);
    // cvCopy(frame, headPose->previousFrame, NULL);

  }
  public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
    mRgba = inputFrame.rgba();
    // convert to Gray scale
    Imgproc.cvtColor(mRgba, img_gray, Imgproc.COLOR_BGR2GRAY);
    // make it binary with threshold=100
    Imgproc.threshold(img_gray, erd, 100, 255, Imgproc.THRESH_OTSU);
    // remove pixel noise by "erode" with structuring element of 9X9
    Mat erode = Imgproc.getStructuringElement(Imgproc.MORPH_ERODE, new Size(9, 9));
    Imgproc.erode(erd, tgt, erode);
    // apply "dilation" to enlarge object
    Mat dilate = Imgproc.getStructuringElement(Imgproc.MORPH_DILATE, new Size(9, 9));
    Imgproc.dilate(tgt, erd, dilate);
    // take a window
    Size s = erd.size();
    int W = (int) s.width;
    int H = (int) s.height;
    Rect r = new Rect(0, H / 2 - 100, W, 200);
    Mat mask = new Mat(s, CvType.CV_8UC1, new Scalar(0, 0, 0));
    rectangle(mask, r.tl(), r.br(), new Scalar(255, 255, 255), -1);
    erd.copyTo(window, mask);

    // find the contours
    Imgproc.findContours(window, contours, dest, 0, 2);
    // find largest contour
    int maxContour = -1;
    double area = 0;
    for (int i = 0; i < contours.size(); i++) {
      double contArea = Imgproc.contourArea(contours.get(i));
      if (contArea > area) {
        area = contArea;
        maxContour = i;
      }
    }
    // form bounding rectangle for largest contour
    Rect rect = null;
    if (maxContour > -1) rect = Imgproc.boundingRect(contours.get(maxContour));
    // position to center
    while (!train) {
      if (rect != null) {
        Imgproc.rectangle(mRgba, rect.tl(), rect.br(), new Scalar(255, 255, 255), 5);
        if ((rect.x + rect.width / 2) > W / 2 - 20 && (rect.x + rect.width / 2) < W / 2 + 20) {
          runOnUiThread(
              new Runnable() {
                @Override
                public void run() {
                  Toast.makeText(getApplicationContext(), "OK", Toast.LENGTH_SHORT).show();
                }
              });
          train = true;
        }
      }
      if (contours != null) contours.clear();
      return mRgba;
    }
    if (train) {
      if (rect != null) {
        Imgproc.rectangle(mRgba, rect.tl(), rect.br(), new Scalar(255, 255, 255), 5);
        // direction of movement
        int thr = 100;
        if ((rect.x + rect.width / 2) < (W / 2 - thr)) {
          // move to the RIGHT
          uHandler.obtainMessage(MainActivity.LEFT).sendToTarget();
        } else {
          if ((rect.x + rect.width / 2) > (W / 2 + thr)) {
            uHandler.obtainMessage(MainActivity.RIGHT).sendToTarget();
          } else {
            uHandler.obtainMessage(MainActivity.FORWARD).sendToTarget();
          }
        }
      } else {
        // stop moving
        uHandler.obtainMessage(MainActivity.STOP).sendToTarget();
      }
    }
    if (contours != null) contours.clear();
    return mRgba;
  }
Beispiel #22
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();
  }
  public Mat onCameraFrame(Mat inputFrame) {
    inputFrame.copyTo(mRgba);

    switch (ImageManipulationsActivity.viewMode) {
      case ImageManipulationsActivity.VIEW_MODE_RGBA:
        break;

      case ImageManipulationsActivity.VIEW_MODE_HIST:
        if ((mSizeRgba == null)
            || (mRgba.cols() != mSizeRgba.width)
            || (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();
        int thikness = (int) (mSizeRgba.width / (mHistSizeNum + 10) / 5);
        if (thikness > 5) thikness = 5;
        int offset = (int) ((mSizeRgba.width - (5 * mHistSizeNum + 4 * 10) * thikness) / 2);
        // RGB
        for (int c = 0; c < 3; c++) {
          Imgproc.calcHist(Arrays.asList(mRgba), mChannels[c], mMat0, mHist, mHistSize, mRanges);
          Core.normalize(mHist, mHist, mSizeRgba.height / 2, 0, Core.NORM_INF);
          mHist.get(0, 0, mBuff);
          for (int h = 0; h < mHistSizeNum; h++) {
            mP1.x = mP2.x = offset + (c * (mHistSizeNum + 10) + h) * thikness;
            mP1.y = mSizeRgba.height - 1;
            mP2.y = mP1.y - 2 - (int) mBuff[h];
            Core.line(mRgba, mP1, mP2, mColorsRGB[c], thikness);
          }
        }
        // Value and Hue
        Imgproc.cvtColor(mRgba, mIntermediateMat, Imgproc.COLOR_RGB2HSV_FULL);
        // Value
        Imgproc.calcHist(
            Arrays.asList(mIntermediateMat), mChannels[2], mMat0, mHist, mHistSize, mRanges);
        Core.normalize(mHist, mHist, mSizeRgba.height / 2, 0, Core.NORM_INF);
        mHist.get(0, 0, mBuff);
        for (int h = 0; h < mHistSizeNum; h++) {
          mP1.x = mP2.x = offset + (3 * (mHistSizeNum + 10) + h) * thikness;
          mP1.y = mSizeRgba.height - 1;
          mP2.y = mP1.y - 2 - (int) mBuff[h];
          Core.line(mRgba, mP1, mP2, mWhilte, thikness);
        }
        // Hue
        Imgproc.calcHist(
            Arrays.asList(mIntermediateMat), mChannels[0], mMat0, mHist, mHistSize, mRanges);
        Core.normalize(mHist, mHist, mSizeRgba.height / 2, 0, Core.NORM_INF);
        mHist.get(0, 0, mBuff);
        for (int h = 0; h < mHistSizeNum; h++) {
          mP1.x = mP2.x = offset + (4 * (mHistSizeNum + 10) + h) * thikness;
          mP1.y = mSizeRgba.height - 1;
          mP2.y = mP1.y - 2 - (int) mBuff[h];
          Core.line(mRgba, mP1, mP2, mColorsHue[h], thikness);
        }
        break;

      case ImageManipulationsActivity.VIEW_MODE_CANNY:
        if ((mRgbaInnerWindow == null)
            || (mGrayInnerWindow == null)
            || (mRgba.cols() != mSizeRgba.width)
            || (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();
        Imgproc.Canny(mRgbaInnerWindow, mIntermediateMat, 80, 90);
        Imgproc.cvtColor(mIntermediateMat, mRgbaInnerWindow, Imgproc.COLOR_GRAY2BGRA, 4);
        break;

      case ImageManipulationsActivity.VIEW_MODE_SOBEL:
        Imgproc.cvtColor(mRgba, mGray, Imgproc.COLOR_RGBA2GRAY);

        if ((mRgbaInnerWindow == null)
            || (mGrayInnerWindow == null)
            || (mRgba.cols() != mSizeRgba.width)
            || (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();

        Imgproc.Sobel(mGrayInnerWindow, mIntermediateMat, CvType.CV_8U, 1, 1);
        Core.convertScaleAbs(mIntermediateMat, mIntermediateMat, 10, 0);
        Imgproc.cvtColor(mIntermediateMat, mRgbaInnerWindow, Imgproc.COLOR_GRAY2BGRA, 4);
        break;

      case ImageManipulationsActivity.VIEW_MODE_SEPIA:
        Core.transform(mRgba, mRgba, mSepiaKernel);
        break;

      case ImageManipulationsActivity.VIEW_MODE_ZOOM:
        if ((mZoomCorner == null)
            || (mZoomWindow == null)
            || (mRgba.cols() != mSizeRgba.width)
            || (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();
        Imgproc.resize(mZoomWindow, mZoomCorner, mZoomCorner.size());

        Size wsize = mZoomWindow.size();
        Core.rectangle(
            mZoomWindow,
            new Point(1, 1),
            new Point(wsize.width - 2, wsize.height - 2),
            new Scalar(255, 0, 0, 255),
            2);
        break;

      case ImageManipulationsActivity.VIEW_MODE_PIXELIZE:
        if ((mRgbaInnerWindow == null)
            || (mRgba.cols() != mSizeRgba.width)
            || (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();
        Imgproc.resize(mRgbaInnerWindow, mIntermediateMat, mSize0, 0.1, 0.1, Imgproc.INTER_NEAREST);
        Imgproc.resize(
            mIntermediateMat, mRgbaInnerWindow, mSizeRgbaInner, 0., 0., Imgproc.INTER_NEAREST);
        break;

      case ImageManipulationsActivity.VIEW_MODE_POSTERIZE:
        if ((mRgbaInnerWindow == null)
            || (mRgba.cols() != mSizeRgba.width)
            || (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();
        /*
        Imgproc.cvtColor(mRgbaInnerWindow, mIntermediateMat, Imgproc.COLOR_RGBA2RGB);
        Imgproc.pyrMeanShiftFiltering(mIntermediateMat, mIntermediateMat, 5, 50);
        Imgproc.cvtColor(mIntermediateMat, mRgbaInnerWindow, Imgproc.COLOR_RGB2RGBA);
        */

        Imgproc.Canny(mRgbaInnerWindow, mIntermediateMat, 80, 90);
        mRgbaInnerWindow.setTo(new Scalar(0, 0, 0, 255), mIntermediateMat);
        Core.convertScaleAbs(mRgbaInnerWindow, mIntermediateMat, 1. / 16, 0);
        Core.convertScaleAbs(mIntermediateMat, mRgbaInnerWindow, 16, 0);
        break;
    }

    return mRgba;
  }