boolean eraseOutsideRoi(ImageProcessor ip, Rectangle r, ImageProcessor mask) {
   int width = ip.getWidth();
   int height = ip.getHeight();
   ip.setRoi(r);
   if (excludeEdgeParticles && polygon != null) {
     ImageStatistics stats = ImageStatistics.getStatistics(ip, MIN_MAX, null);
     if (fillColor >= stats.min && fillColor <= stats.max) {
       double replaceColor = level1 - 1.0;
       if (replaceColor < 0.0 || replaceColor == fillColor) {
         replaceColor = level2 + 1.0;
         int maxColor = imageType == BYTE ? 255 : 65535;
         if (replaceColor > maxColor || replaceColor == fillColor) {
           IJ.error("Particle Analyzer", "Unable to remove edge particles");
           return false;
         }
       }
       for (int y = minY; y < maxY; y++) {
         for (int x = minX; x < maxX; x++) {
           int v = ip.getPixel(x, y);
           if (v == fillColor) ip.putPixel(x, y, (int) replaceColor);
         }
       }
     }
   }
   ip.setValue(fillColor);
   if (mask != null) {
     mask = mask.duplicate();
     mask.invert();
     ip.fill(mask);
   }
   ip.setRoi(0, 0, r.x, height);
   ip.fill();
   ip.setRoi(r.x, 0, r.width, r.y);
   ip.fill();
   ip.setRoi(r.x, r.y + r.height, r.width, height - (r.y + r.height));
   ip.fill();
   ip.setRoi(r.x + r.width, 0, width - (r.x + r.width), height);
   ip.fill();
   ip.resetRoi();
   // IJ.log("erase: "+fillColor+"	"+level1+"	"+level2+"	"+excludeEdgeParticles);
   // (new ImagePlus("ip2", ip.duplicate())).show();
   return true;
 }
예제 #2
0
  /** Ask for parameters and then execute. */
  public void run(String arg) {
    // 1 - Obtain the currently active image:
    ImagePlus imp = IJ.getImage();

    if (null == imp) {
      IJ.showMessage("There must be at least one image open");
      return;
    }

    if (imp.getBitDepth() != 8) {
      IJ.showMessage("Error", "Only 8-bit images are supported");
      return;
    }

    // 2 - Ask for parameters:
    GenericDialog gd = new GenericDialog("Auto Local Threshold");
    String[] methods = {
      "Try all",
      "Bernsen",
      "Contrast",
      "Mean",
      "Median",
      "MidGrey",
      "Niblack",
      "Otsu",
      "Phansalkar",
      "Sauvola"
    };
    gd.addMessage("Auto Local Threshold v1.5");
    gd.addChoice("Method", methods, methods[0]);
    gd.addNumericField("Radius", 15, 0);
    gd.addMessage("Special paramters (if different from default)");
    gd.addNumericField("Parameter_1", 0, 0);
    gd.addNumericField("Parameter_2", 0, 0);
    gd.addCheckbox("White objects on black background", true);
    if (imp.getStackSize() > 1) {
      gd.addCheckbox("Stack", false);
    }
    gd.addMessage("Thresholded result is always shown in white [255].");
    gd.showDialog();
    if (gd.wasCanceled()) return;

    // 3 - Retrieve parameters from the dialog
    String myMethod = gd.getNextChoice();
    int radius = (int) gd.getNextNumber();
    double par1 = (double) gd.getNextNumber();
    double par2 = (double) gd.getNextNumber();
    boolean doIwhite = gd.getNextBoolean();
    boolean doIstack = false;

    int stackSize = imp.getStackSize();
    if (stackSize > 1) doIstack = gd.getNextBoolean();

    // 4 - Execute!
    // long start = System.currentTimeMillis();
    if (myMethod.equals("Try all")) {
      ImageProcessor ip = imp.getProcessor();
      int xe = ip.getWidth();
      int ye = ip.getHeight();
      int ml = methods.length;
      ImagePlus imp2, imp3;
      ImageStack tstack = null, stackNew;
      if (stackSize > 1 && doIstack) {
        boolean doItAnyway = true;
        if (stackSize > 25) {
          YesNoCancelDialog d =
              new YesNoCancelDialog(
                  IJ.getInstance(),
                  "Auto Local Threshold",
                  "You might run out of memory.\n \nDisplay "
                      + stackSize
                      + " slices?\n \n \'No\' will process without display and\noutput results to the log window.");
          if (!d.yesPressed()) {
            //						doIlog=true; //will show in the log window
            doItAnyway = false;
          }
          if (d.cancelPressed()) return;
        }

        for (int j = 1; j <= stackSize; j++) {
          imp.setSlice(j);
          ip = imp.getProcessor();
          tstack = new ImageStack(xe, ye);
          for (int k = 1; k < ml; k++) tstack.addSlice(methods[k], ip.duplicate());
          imp2 = new ImagePlus("Auto Threshold", tstack);
          imp2.updateAndDraw();

          for (int k = 1; k < ml; k++) {
            imp2.setSlice(k);
            Object[] result = exec(imp2, methods[k], radius, par1, par2, doIwhite);
          }
          // if (doItAnyway){
          CanvasResizer cr = new CanvasResizer();
          stackNew = cr.expandStack(tstack, (xe + 2), (ye + 18), 1, 1);
          imp3 = new ImagePlus("Auto Threshold", stackNew);
          imp3.updateAndDraw();
          MontageMaker mm = new MontageMaker();
          mm.makeMontage(imp3, 3, 3, 1.0, 1, (ml - 1), 1, 0, true); // 3 columns and 3 rows
        }
        imp.setSlice(1);
        // if (doItAnyway)
        IJ.run("Images to Stack", "method=[Copy (center)] title=Montage");
        return;
      } else { // single image try all
        tstack = new ImageStack(xe, ye);
        for (int k = 1; k < ml; k++) tstack.addSlice(methods[k], ip.duplicate());
        imp2 = new ImagePlus("Auto Threshold", tstack);
        imp2.updateAndDraw();

        for (int k = 1; k < ml; k++) {
          imp2.setSlice(k);
          // IJ.log("analyzing slice with "+methods[k]);
          Object[] result = exec(imp2, methods[k], radius, par1, par2, doIwhite);
        }
        // imp2.setSlice(1);
        CanvasResizer cr = new CanvasResizer();
        stackNew = cr.expandStack(tstack, (xe + 2), (ye + 18), 1, 1);
        imp3 = new ImagePlus("Auto Threshold", stackNew);
        imp3.updateAndDraw();
        MontageMaker mm = new MontageMaker();
        mm.makeMontage(imp3, 3, 3, 1.0, 1, (ml - 1), 1, 0, true);
        return;
      }
    } else { // selected a method
      if (stackSize > 1 && doIstack) { // whole stack
        //				if (doIstackHistogram) {// one global histogram
        //					Object[] result = exec(imp, myMethod, noWhite, noBlack, doIwhite, doIset, doIlog,
        // doIstackHistogram );
        //				}
        //				else{ // slice by slice
        for (int k = 1; k <= stackSize; k++) {
          imp.setSlice(k);
          Object[] result = exec(imp, myMethod, radius, par1, par2, doIwhite);
        }
        //				}
        imp.setSlice(1);
      } else { // just one slice
        Object[] result = exec(imp, myMethod, radius, par1, par2, doIwhite);
      }
      // 5 - If all went well, show the image:
      // not needed here as the source image is binarised
    }
  }
  /**
   * Performs particle analysis on the specified ImagePlus and ImageProcessor. Returns false if
   * there is an error.
   */
  public boolean analyze(ImagePlus imp, ImageProcessor ip) {
    if (this.imp == null) this.imp = imp;
    showResults = (options & SHOW_RESULTS) != 0;
    excludeEdgeParticles = (options & EXCLUDE_EDGE_PARTICLES) != 0;
    resetCounter = (options & CLEAR_WORKSHEET) != 0;
    showProgress = (options & SHOW_PROGRESS) != 0;
    floodFill = (options & INCLUDE_HOLES) == 0;
    recordStarts = (options & RECORD_STARTS) != 0;
    addToManager = (options & ADD_TO_MANAGER) != 0;
    displaySummary = (options & DISPLAY_SUMMARY) != 0;
    inSituShow = (options & IN_SITU_SHOW) != 0;
    outputImage = null;
    ip.snapshot();
    ip.setProgressBar(null);
    if (Analyzer.isRedirectImage()) {
      redirectImp = Analyzer.getRedirectImage(imp);
      if (redirectImp == null) return false;
      int depth = redirectImp.getStackSize();
      if (depth > 1 && depth == imp.getStackSize()) {
        ImageStack redirectStack = redirectImp.getStack();
        redirectIP = redirectStack.getProcessor(imp.getCurrentSlice());
      } else redirectIP = redirectImp.getProcessor();
    } else if (imp.getType() == ImagePlus.COLOR_RGB) {
      ImagePlus original = (ImagePlus) imp.getProperty("OriginalImage");
      if (original != null
          && original.getWidth() == imp.getWidth()
          && original.getHeight() == imp.getHeight()) {
        redirectImp = original;
        redirectIP = original.getProcessor();
      }
    }
    if (!setThresholdLevels(imp, ip)) return false;
    width = ip.getWidth();
    height = ip.getHeight();
    if (!(showChoice == NOTHING || showChoice == OVERLAY_OUTLINES || showChoice == OVERLAY_MASKS)) {
      blackBackground = Prefs.blackBackground && inSituShow;
      if (slice == 1) outlines = new ImageStack(width, height);
      if (showChoice == ROI_MASKS) drawIP = new ShortProcessor(width, height);
      else drawIP = new ByteProcessor(width, height);
      drawIP.setLineWidth(lineWidth);
      if (showChoice == ROI_MASKS) {
      } // Place holder for now...
      else if (showChoice == MASKS && !blackBackground) drawIP.invertLut();
      else if (showChoice == OUTLINES) {
        if (!inSituShow) {
          if (customLut == null) makeCustomLut();
          drawIP.setColorModel(customLut);
        }
        drawIP.setFont(new Font("SansSerif", Font.PLAIN, fontSize));
        if (fontSize > 12 && inSituShow) drawIP.setAntialiasedText(true);
      }
      outlines.addSlice(null, drawIP);

      if (showChoice == ROI_MASKS || blackBackground) {
        drawIP.setColor(Color.black);
        drawIP.fill();
        drawIP.setColor(Color.white);
      } else {
        drawIP.setColor(Color.white);
        drawIP.fill();
        drawIP.setColor(Color.black);
      }
    }
    calibration = redirectImp != null ? redirectImp.getCalibration() : imp.getCalibration();

    if (rt == null) {
      rt = Analyzer.getResultsTable();
      analyzer = new Analyzer(imp);
    } else analyzer = new Analyzer(imp, measurements, rt);
    if (resetCounter && slice == 1) {
      if (!Analyzer.resetCounter()) return false;
    }
    beginningCount = Analyzer.getCounter();

    byte[] pixels = null;
    if (ip instanceof ByteProcessor) pixels = (byte[]) ip.getPixels();
    if (r == null) {
      r = ip.getRoi();
      mask = ip.getMask();
      if (displaySummary) {
        if (mask != null) totalArea = ImageStatistics.getStatistics(ip, AREA, calibration).area;
        else totalArea = r.width * calibration.pixelWidth * r.height * calibration.pixelHeight;
      }
    }
    minX = r.x;
    maxX = r.x + r.width;
    minY = r.y;
    maxY = r.y + r.height;
    if (r.width < width || r.height < height || mask != null) {
      if (!eraseOutsideRoi(ip, r, mask)) return false;
    }
    int offset;
    double value;
    int inc = Math.max(r.height / 25, 1);
    int mi = 0;
    ImageWindow win = imp.getWindow();
    if (win != null) win.running = true;
    if (measurements == 0) measurements = Analyzer.getMeasurements();
    if (showChoice == ELLIPSES) measurements |= ELLIPSE;
    measurements &= ~LIMIT; // ignore "Limit to Threshold"
    roiNeedsImage =
        (measurements & PERIMETER) != 0
            || (measurements & SHAPE_DESCRIPTORS) != 0
            || (measurements & FERET) != 0;
    particleCount = 0;
    wand = new Wand(ip);
    pf = new PolygonFiller();
    if (floodFill) {
      ImageProcessor ipf = ip.duplicate();
      ipf.setValue(fillColor);
      ff = new FloodFiller(ipf);
    }
    roiType = Wand.allPoints() ? Roi.FREEROI : Roi.TRACED_ROI;

    for (int y = r.y; y < (r.y + r.height); y++) {
      offset = y * width;
      for (int x = r.x; x < (r.x + r.width); x++) {
        if (pixels != null) value = pixels[offset + x] & 255;
        else if (imageType == SHORT) value = ip.getPixel(x, y);
        else value = ip.getPixelValue(x, y);
        if (value >= level1 && value <= level2) analyzeParticle(x, y, imp, ip);
      }
      if (showProgress && ((y % inc) == 0)) IJ.showProgress((double) (y - r.y) / r.height);
      if (win != null) canceled = !win.running;
      if (canceled) {
        Macro.abort();
        break;
      }
    }
    if (showProgress) IJ.showProgress(1.0);
    if (showResults) rt.updateResults();
    imp.killRoi();
    ip.resetRoi();
    ip.reset();
    if (displaySummary && IJ.getInstance() != null) updateSliceSummary();
    if (addToManager && roiManager != null) roiManager.setEditMode(imp, true);
    maxParticleCount = (particleCount > maxParticleCount) ? particleCount : maxParticleCount;
    totalCount += particleCount;
    if (!canceled) showResults();
    return true;
  }
예제 #4
0
  /*------------------------------------------------------------------*/
  void doIt(ImageProcessor ip) {
    int width = ip.getWidth();
    int height = ip.getHeight();
    double hLine[] = new double[width];
    double vLine[] = new double[height];

    if (!(ip.getPixels() instanceof float[])) {
      throw new IllegalArgumentException("Float image required");
    }
    switch (operation) {
      case GRADIENT_MAGNITUDE:
        {
          ImageProcessor h = ip.duplicate();
          ImageProcessor v = ip.duplicate();
          float[] floatPixels = (float[]) ip.getPixels();
          float[] floatPixelsH = (float[]) h.getPixels();
          float[] floatPixelsV = (float[]) v.getPixels();

          getHorizontalGradient(h, FLT_EPSILON);
          getVerticalGradient(v, FLT_EPSILON);
          for (int y = 0, k = 0; (y < height); y++) {
            for (int x = 0; (x < width); x++, k++) {
              floatPixels[k] =
                  (float)
                      Math.sqrt(
                          floatPixelsH[k] * floatPixelsH[k] + floatPixelsV[k] * floatPixelsV[k]);
            }
            stepProgressBar();
          }
        }
        break;
      case GRADIENT_DIRECTION:
        {
          ImageProcessor h = ip.duplicate();
          ImageProcessor v = ip.duplicate();
          float[] floatPixels = (float[]) ip.getPixels();
          float[] floatPixelsH = (float[]) h.getPixels();
          float[] floatPixelsV = (float[]) v.getPixels();

          getHorizontalGradient(h, FLT_EPSILON);
          getVerticalGradient(v, FLT_EPSILON);
          for (int y = 0, k = 0; (y < height); y++) {
            for (int x = 0; (x < width); x++, k++) {
              floatPixels[k] = (float) Math.atan2(floatPixelsH[k], floatPixelsV[k]);
            }
            stepProgressBar();
          }
        }
        break;
      case LAPLACIAN:
        {
          ImageProcessor hh = ip.duplicate();
          ImageProcessor vv = ip.duplicate();
          float[] floatPixels = (float[]) ip.getPixels();
          float[] floatPixelsHH = (float[]) hh.getPixels();
          float[] floatPixelsVV = (float[]) vv.getPixels();

          getHorizontalHessian(hh, FLT_EPSILON);
          getVerticalHessian(vv, FLT_EPSILON);
          for (int y = 0, k = 0; (y < height); y++) {
            for (int x = 0; (x < width); x++, k++) {
              floatPixels[k] = (float) (floatPixelsHH[k] + floatPixelsVV[k]);
            }
            stepProgressBar();
          }
        }
        break;
      case LARGEST_HESSIAN:
        {
          ImageProcessor hh = ip.duplicate();
          ImageProcessor vv = ip.duplicate();
          ImageProcessor hv = ip.duplicate();
          float[] floatPixels = (float[]) ip.getPixels();
          float[] floatPixelsHH = (float[]) hh.getPixels();
          float[] floatPixelsVV = (float[]) vv.getPixels();
          float[] floatPixelsHV = (float[]) hv.getPixels();

          getHorizontalHessian(hh, FLT_EPSILON);
          getVerticalHessian(vv, FLT_EPSILON);
          getCrossHessian(hv, FLT_EPSILON);
          for (int y = 0, k = 0; (y < height); y++) {
            for (int x = 0; (x < width); x++, k++) {
              floatPixels[k] =
                  (float)
                      (0.5
                          * (floatPixelsHH[k]
                              + floatPixelsVV[k]
                              + Math.sqrt(
                                  4.0 * floatPixelsHV[k] * floatPixelsHV[k]
                                      + (floatPixelsHH[k] - floatPixelsVV[k])
                                          * (floatPixelsHH[k] - floatPixelsVV[k]))));
            }
            stepProgressBar();
          }
        }
        break;
      case SMALLEST_HESSIAN:
        {
          ImageProcessor hh = ip.duplicate();
          ImageProcessor vv = ip.duplicate();
          ImageProcessor hv = ip.duplicate();
          float[] floatPixels = (float[]) ip.getPixels();
          float[] floatPixelsHH = (float[]) hh.getPixels();
          float[] floatPixelsVV = (float[]) vv.getPixels();
          float[] floatPixelsHV = (float[]) hv.getPixels();

          getHorizontalHessian(hh, FLT_EPSILON);
          getVerticalHessian(vv, FLT_EPSILON);
          getCrossHessian(hv, FLT_EPSILON);
          for (int y = 0, k = 0; (y < height); y++) {
            for (int x = 0; (x < width); x++, k++) {
              floatPixels[k] =
                  (float)
                      (0.5
                          * (floatPixelsHH[k]
                              + floatPixelsVV[k]
                              - Math.sqrt(
                                  4.0 * floatPixelsHV[k] * floatPixelsHV[k]
                                      + (floatPixelsHH[k] - floatPixelsVV[k])
                                          * (floatPixelsHH[k] - floatPixelsVV[k]))));
            }
            stepProgressBar();
          }
        }
        break;
      case HESSIAN_ORIENTATION:
        {
          ImageProcessor hh = ip.duplicate();
          ImageProcessor vv = ip.duplicate();
          ImageProcessor hv = ip.duplicate();
          float[] floatPixels = (float[]) ip.getPixels();
          float[] floatPixelsHH = (float[]) hh.getPixels();
          float[] floatPixelsVV = (float[]) vv.getPixels();
          float[] floatPixelsHV = (float[]) hv.getPixels();

          getHorizontalHessian(hh, FLT_EPSILON);
          getVerticalHessian(vv, FLT_EPSILON);
          getCrossHessian(hv, FLT_EPSILON);
          for (int y = 0, k = 0; (y < height); y++) {
            for (int x = 0; (x < width); x++, k++) {
              if (floatPixelsHV[k] < 0.0) {
                floatPixels[k] =
                    (float)
                        (-0.5
                            * Math.acos(
                                (floatPixelsHH[k] - floatPixelsVV[k])
                                    / Math.sqrt(
                                        4.0 * floatPixelsHV[k] * floatPixelsHV[k]
                                            + (floatPixelsHH[k] - floatPixelsVV[k])
                                                * (floatPixelsHH[k] - floatPixelsVV[k]))));
              } else {
                floatPixels[k] =
                    (float)
                        (0.5
                            * Math.acos(
                                (floatPixelsHH[k] - floatPixelsVV[k])
                                    / Math.sqrt(
                                        4.0 * floatPixelsHV[k] * floatPixelsHV[k]
                                            + (floatPixelsHH[k] - floatPixelsVV[k])
                                                * (floatPixelsHH[k] - floatPixelsVV[k]))));
              }
            }
            stepProgressBar();
          }
        }
        break;
      default:
        throw new IllegalArgumentException("Invalid operation");
    }
    ip.resetMinAndMax();
    imp.updateAndDraw();
  } /* end doIt */