void createMaskFromThreshold(ImagePlus imp) {
ImageProcessor ip = imp.getProcessor();
if (ip.getMinThreshold() == ImageProcessor.NO_THRESHOLD) {
IJ.error("Create Mask", "Area selection or thresholded image required");
return;
}
double t1 = ip.getMinThreshold();
double t2 = ip.getMaxThreshold();
IJ.run("Duplicate...", "title=mask");
ImagePlus imp2 = WindowManager.getCurrentImage();
ImageProcessor ip2 = imp2.getProcessor();
ip2.setThreshold(t1, t2, ImageProcessor.NO_LUT_UPDATE);
IJ.run("Convert to Mask");
}
void createMask(ImagePlus imp) {
Roi roi = imp.getRoi();
boolean useInvertingLut = Prefs.useInvertingLut;
Prefs.useInvertingLut = false;
if (roi == null || !(roi.isArea() || roi.getType() == Roi.POINT)) {
createMaskFromThreshold(imp);
Prefs.useInvertingLut = useInvertingLut;
return;
}
ImagePlus maskImp = null;
Frame frame = WindowManager.getFrame("Mask");
if (frame != null && (frame instanceof ImageWindow))
maskImp = ((ImageWindow) frame).getImagePlus();
if (maskImp == null) {
ImageProcessor ip = new ByteProcessor(imp.getWidth(), imp.getHeight());
if (!Prefs.blackBackground) ip.invertLut();
maskImp = new ImagePlus("Mask", ip);
maskImp.show();
}
ImageProcessor ip = maskImp.getProcessor();
ip.setRoi(roi);
ip.setValue(255);
ip.fill(ip.getMask());
maskImp.updateAndDraw();
Prefs.useInvertingLut = useInvertingLut;
}
void createEllipse(ImagePlus imp) {
IJ.showStatus("Fitting ellipse");
Roi roi = imp.getRoi();
if (roi == null) {
noRoi("Fit Ellipse");
return;
}
if (roi.isLine()) {
IJ.error("Fit Ellipse", "\"Fit Ellipse\" does not work with line selections");
return;
}
ImageProcessor ip = imp.getProcessor();
ip.setRoi(roi);
int options = Measurements.CENTROID + Measurements.ELLIPSE;
ImageStatistics stats = ImageStatistics.getStatistics(ip, options, null);
double dx = stats.major * Math.cos(stats.angle / 180.0 * Math.PI) / 2.0;
double dy = -stats.major * Math.sin(stats.angle / 180.0 * Math.PI) / 2.0;
double x1 = stats.xCentroid - dx;
double x2 = stats.xCentroid + dx;
double y1 = stats.yCentroid - dy;
double y2 = stats.yCentroid + dy;
double aspectRatio = stats.minor / stats.major;
imp.killRoi();
imp.setRoi(new EllipseRoi(x1, y1, x2, y2, aspectRatio));
}
void setHistogram(ImagePlus imp, int j) {
ImageProcessor ip = imp.getProcessor();
ImageStatistics stats = ImageStatistics.getStatistics(ip, AREA + MODE, null);
int maxCount2 = 0;
histogram = stats.histogram;
for (int i = 0; i < stats.nBins; i++)
if ((histogram[i] > maxCount2) && (i != stats.mode)) maxCount2 = histogram[i];
hmax = stats.maxCount;
if ((hmax > (maxCount2 * 1.5)) && (maxCount2 != 0)) { // GL 1.5 was 2
hmax = (int) (maxCount2 * 1.1); // GL 1.1 was 1.5
histogram[stats.mode] = hmax;
}
os = null;
ColorModel cm = ip.getColorModel();
if (!(cm instanceof IndexColorModel)) return;
IndexColorModel icm = (IndexColorModel) cm;
int mapSize = icm.getMapSize();
if (mapSize != 256) return;
byte[] r = new byte[256];
byte[] g = new byte[256];
byte[] b = new byte[256];
icm.getReds(r);
icm.getGreens(g);
icm.getBlues(b);
hColors = new Color[256];
if (isRGB) {
if (j == 0) {
for (int i = 0; i < 256; i++) hColors[i] = new Color(i & 255, 0 & 255, 0 & 255);
} else if (j == 1) {
for (int i = 0; i < 256; i++) hColors[i] = new Color(0 & 255, i & 255, 0 & 255);
} else if (j == 2) {
for (int i = 0; i < 256; i++) hColors[i] = new Color(0 & 255, 0 & 255, i & 255);
}
} else {
if (j == 0) {
for (int i = 0; i < 256; i++) hColors[i] = new Color(r[i] & 255, g[i] & 255, b[i] & 255);
} else if (j == 1) {
for (int i = 0; i < 256; i++)
// hColors[i] = new Color(127-i/2&255, 127+i/2&255, 127-i/2&255);
hColors[i] = new Color(192 - i / 4 & 255, 192 + i / 4 & 255, 192 - i / 4 & 255);
} else if (j == 2) {
for (int i = 0; i < 256; i++) hColors[i] = new Color(i & 255, i & 255, 0 & 255);
}
}
}
void createSelectionFromMask(ImagePlus imp) {
ImageProcessor ip = imp.getProcessor();
if (ip.getMinThreshold() != ImageProcessor.NO_THRESHOLD) {
IJ.runPlugIn("ij.plugin.filter.ThresholdToSelection", "");
return;
}
if (!ip.isBinary()) {
IJ.error(
"Create Selection",
"This command creates a composite selection from\n"
+ "a mask (8-bit binary image with white background)\n"
+ "or from an image that has been thresholded using\n"
+ "the Image>Adjust>Threshold tool. The current\n"
+ "image is not a mask and has not been thresholded.");
return;
}
int threshold = ip.isInvertedLut() ? 255 : 0;
ip.setThreshold(threshold, threshold, ImageProcessor.NO_LUT_UPDATE);
IJ.runPlugIn("ij.plugin.filter.ThresholdToSelection", "");
}
void createMask(ImagePlus imp) {
Roi roi = imp.getRoi();
boolean useInvertingLut = Prefs.useInvertingLut;
Prefs.useInvertingLut = false;
boolean selectAll =
roi != null
&& roi.getType() == Roi.RECTANGLE
&& roi.getBounds().width == imp.getWidth()
&& roi.getBounds().height == imp.getHeight()
&& imp.isThreshold();
if (roi == null || !(roi.isArea() || roi.getType() == Roi.POINT) || selectAll) {
createMaskFromThreshold(imp);
Prefs.useInvertingLut = useInvertingLut;
return;
}
ImagePlus maskImp = null;
Frame frame = WindowManager.getFrame("Mask");
if (frame != null && (frame instanceof ImageWindow))
maskImp = ((ImageWindow) frame).getImagePlus();
if (maskImp == null) {
ImageProcessor ip = new ByteProcessor(imp.getWidth(), imp.getHeight());
if (!Prefs.blackBackground) ip.invertLut();
maskImp = new ImagePlus("Mask", ip);
maskImp.show();
}
ImageProcessor ip = maskImp.getProcessor();
ip.setRoi(roi);
ip.setValue(255);
ip.fill(ip.getMask());
Calibration cal = imp.getCalibration();
if (cal.scaled()) {
Calibration cal2 = maskImp.getCalibration();
cal2.pixelWidth = cal.pixelWidth;
cal2.pixelHeight = cal.pixelHeight;
cal2.setUnit(cal.getUnit());
}
maskImp.updateAndRepaintWindow();
Prefs.useInvertingLut = useInvertingLut;
}
/*
if selection is closed shape, create a circle with the same area and centroid, otherwise use<br>
the Pratt method to fit a circle to the points that define the line or multi-point selection.<br>
Reference: Pratt V., Direct least-squares fitting of algebraic surfaces", Computer Graphics, Vol. 21, pages 145-152 (1987).<br>
Original code: Nikolai Chernov's MATLAB script for Newton-based Pratt fit.<br>
(http://www.math.uab.edu/~chernov/cl/MATLABcircle.html)<br>
Java version: https://github.com/mdoube/BoneJ/blob/master/src/org/doube/geometry/FitCircle.java<br>
@authors Nikolai Chernov, Michael Doube, Ved Sharma
*/
void fitCircle(ImagePlus imp) {
Roi roi = imp.getRoi();
if (roi == null) {
noRoi("Fit Circle");
return;
}
if (roi.isArea()) { // create circle with the same area and centroid
ImageProcessor ip = imp.getProcessor();
ip.setRoi(roi);
ImageStatistics stats =
ImageStatistics.getStatistics(ip, Measurements.AREA + Measurements.CENTROID, null);
double r = Math.sqrt(stats.pixelCount / Math.PI);
imp.killRoi();
int d = (int) Math.round(2.0 * r);
IJ.makeOval(
(int) Math.round(stats.xCentroid - r), (int) Math.round(stats.yCentroid - r), d, d);
return;
}
Polygon poly = roi.getPolygon();
int n = poly.npoints;
int[] x = poly.xpoints;
int[] y = poly.ypoints;
if (n < 3) {
IJ.error("Fit Circle", "At least 3 points are required to fit a circle.");
return;
}
// calculate point centroid
double sumx = 0, sumy = 0;
for (int i = 0; i < n; i++) {
sumx = sumx + poly.xpoints[i];
sumy = sumy + poly.ypoints[i];
}
double meanx = sumx / n;
double meany = sumy / n;
// calculate moments
double[] X = new double[n], Y = new double[n];
double Mxx = 0, Myy = 0, Mxy = 0, Mxz = 0, Myz = 0, Mzz = 0;
for (int i = 0; i < n; i++) {
X[i] = x[i] - meanx;
Y[i] = y[i] - meany;
double Zi = X[i] * X[i] + Y[i] * Y[i];
Mxy = Mxy + X[i] * Y[i];
Mxx = Mxx + X[i] * X[i];
Myy = Myy + Y[i] * Y[i];
Mxz = Mxz + X[i] * Zi;
Myz = Myz + Y[i] * Zi;
Mzz = Mzz + Zi * Zi;
}
Mxx = Mxx / n;
Myy = Myy / n;
Mxy = Mxy / n;
Mxz = Mxz / n;
Myz = Myz / n;
Mzz = Mzz / n;
// calculate the coefficients of the characteristic polynomial
double Mz = Mxx + Myy;
double Cov_xy = Mxx * Myy - Mxy * Mxy;
double Mxz2 = Mxz * Mxz;
double Myz2 = Myz * Myz;
double A2 = 4 * Cov_xy - 3 * Mz * Mz - Mzz;
double A1 = Mzz * Mz + 4 * Cov_xy * Mz - Mxz2 - Myz2 - Mz * Mz * Mz;
double A0 = Mxz2 * Myy + Myz2 * Mxx - Mzz * Cov_xy - 2 * Mxz * Myz * Mxy + Mz * Mz * Cov_xy;
double A22 = A2 + A2;
double epsilon = 1e-12;
double ynew = 1e+20;
int IterMax = 20;
double xnew = 0;
int iterations = 0;
// Newton's method starting at x=0
for (int iter = 1; iter <= IterMax; iter++) {
iterations = iter;
double yold = ynew;
ynew = A0 + xnew * (A1 + xnew * (A2 + 4. * xnew * xnew));
if (Math.abs(ynew) > Math.abs(yold)) {
if (IJ.debugMode) IJ.log("Fit Circle: wrong direction: |ynew| > |yold|");
xnew = 0;
break;
}
double Dy = A1 + xnew * (A22 + 16 * xnew * xnew);
double xold = xnew;
xnew = xold - ynew / Dy;
if (Math.abs((xnew - xold) / xnew) < epsilon) break;
if (iter >= IterMax) {
if (IJ.debugMode) IJ.log("Fit Circle: will not converge");
xnew = 0;
}
if (xnew < 0) {
if (IJ.debugMode) IJ.log("Fit Circle: negative root: x = " + xnew);
xnew = 0;
}
}
if (IJ.debugMode)
IJ.log("Fit Circle: n=" + n + ", xnew=" + IJ.d2s(xnew, 2) + ", iterations=" + iterations);
// calculate the circle parameters
double DET = xnew * xnew - xnew * Mz + Cov_xy;
double CenterX = (Mxz * (Myy - xnew) - Myz * Mxy) / (2 * DET);
double CenterY = (Myz * (Mxx - xnew) - Mxz * Mxy) / (2 * DET);
double radius = Math.sqrt(CenterX * CenterX + CenterY * CenterY + Mz + 2 * xnew);
if (Double.isNaN(radius)) {
IJ.error("Fit Circle", "Points are collinear.");
return;
}
CenterX = CenterX + meanx;
CenterY = CenterY + meany;
imp.killRoi();
IJ.makeOval(
(int) Math.round(CenterX - radius),
(int) Math.round(CenterY - radius),
(int) Math.round(2 * radius),
(int) Math.round(2 * radius));
}
private void makeBand(ImagePlus imp) {
Roi roi = imp.getRoi();
if (roi == null) {
noRoi("Make Band");
return;
}
if (!roi.isArea()) {
IJ.error("Make Band", "Area selection required");
return;
}
Calibration cal = imp.getCalibration();
double pixels = bandSize;
double size = pixels * cal.pixelWidth;
int decimalPlaces = 0;
if ((int) size != size) decimalPlaces = 2;
GenericDialog gd = new GenericDialog("Make Band");
gd.addNumericField("Band Size:", size, decimalPlaces, 4, cal.getUnits());
gd.showDialog();
if (gd.wasCanceled()) return;
size = gd.getNextNumber();
if (Double.isNaN(size)) {
IJ.error("Make Band", "invalid number");
return;
}
int n = (int) Math.round(size / cal.pixelWidth);
if (n > 255) {
IJ.error("Make Band", "Cannot make bands wider that 255 pixels");
return;
}
int width = imp.getWidth();
int height = imp.getHeight();
Rectangle r = roi.getBounds();
ImageProcessor ip = roi.getMask();
if (ip == null) {
ip = new ByteProcessor(r.width, r.height);
ip.invert();
}
ImageProcessor mask = new ByteProcessor(width, height);
mask.insert(ip, r.x, r.y);
ImagePlus edm = new ImagePlus("mask", mask);
boolean saveBlackBackground = Prefs.blackBackground;
Prefs.blackBackground = false;
IJ.run(edm, "Distance Map", "");
Prefs.blackBackground = saveBlackBackground;
ip = edm.getProcessor();
ip.setThreshold(0, n, ImageProcessor.NO_LUT_UPDATE);
int xx = -1, yy = -1;
for (int x = r.x; x < r.x + r.width; x++) {
for (int y = r.y; y < r.y + r.height; y++) {
if (ip.getPixel(x, y) < n) {
xx = x;
yy = y;
break;
}
}
if (xx >= 0 || yy >= 0) break;
}
int count = IJ.doWand(edm, xx, yy, 0, null);
if (count <= 0) {
IJ.error("Make Band", "Unable to make band");
return;
}
ShapeRoi roi2 = new ShapeRoi(edm.getRoi());
if (!(roi instanceof ShapeRoi)) roi = new ShapeRoi(roi);
ShapeRoi roi1 = (ShapeRoi) roi;
roi2 = roi2.not(roi1);
imp.setRoi(roi2);
bandSize = n;
}
ImageProcessor setup(ImagePlus imp) {
ImageProcessor ip;
int type = imp.getType();
if (type != ImagePlus.COLOR_RGB) return null;
ip = imp.getProcessor();
int id = imp.getID();
int slice = imp.getCurrentSlice();
if ((id != previousImageID) | (slice != previousSlice) | (flag)) {
flag = false; // if true, flags a change from HSB to RGB or viceversa
numSlices = imp.getStackSize();
stack = imp.getStack();
width = stack.getWidth();
height = stack.getHeight();
numPixels = width * height;
hSource = new byte[numPixels];
sSource = new byte[numPixels];
bSource = new byte[numPixels];
// restore = (int[])ip.getPixelsCopy(); //This runs into trouble sometimes, so do it the
// long way:
int[] temp = (int[]) ip.getPixels();
restore = new int[numPixels];
for (int i = 0; i < numPixels; i++) restore[i] = temp[i];
fillMask = new int[numPixels];
// Get hsb or rgb from image.
ColorProcessor cp = (ColorProcessor) ip;
IJ.showStatus("Gathering data");
if (isRGB) cp.getRGB(hSource, sSource, bSource);
else cp.getHSB(hSource, sSource, bSource);
IJ.showStatus("done");
// Create a spectrum ColorModel for the Hue histogram plot.
Color c;
byte[] reds = new byte[256];
byte[] greens = new byte[256];
byte[] blues = new byte[256];
for (int i = 0; i < 256; i++) {
c = Color.getHSBColor(i / 255f, 1f, 1f);
reds[i] = (byte) c.getRed();
greens[i] = (byte) c.getGreen();
blues[i] = (byte) c.getBlue();
}
ColorModel cm = new IndexColorModel(8, 256, reds, greens, blues);
// Make an image with just the hue from the RGB image and the spectrum LUT.
// This is just for a hue histogram for the plot. Do not show it.
// ByteProcessor bpHue = new ByteProcessor(width,height,h,cm);
ByteProcessor bpHue = new ByteProcessor(width, height, hSource, cm);
ImagePlus impHue = new ImagePlus("Hue", bpHue);
// impHue.show();
ByteProcessor bpSat = new ByteProcessor(width, height, sSource, cm);
ImagePlus impSat = new ImagePlus("Sat", bpSat);
// impSat.show();
ByteProcessor bpBri = new ByteProcessor(width, height, bSource, cm);
ImagePlus impBri = new ImagePlus("Bri", bpBri);
// impBri.show();
plot.setHistogram(impHue, 0);
splot.setHistogram(impSat, 1);
bplot.setHistogram(impBri, 2);
updateLabels();
updatePlot();
updateScrollBars();
imp.updateAndDraw();
}
previousImageID = id;
previousSlice = slice;
return ip;
}