Esempio n. 1
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  /**
   * Constructor records the calling instance of DisplayWindow and loads and trains the knn
   * classifier.
   *
   * @param instance The instace of DisplayWindow which instantiated this class
   */
  public ImageProcessor(DisplayWindow instance) {
    this.callingInstance = instance;

    // Load and train knn classifier
    TrainingData td = new TrainingData();
    knn = new CvKNearest();
    knn.train(td.trainingData, td.trainingLabels);
  }
Esempio n. 2
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  /**
   * 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);
        }
      }
    }
  }