/**
* calculates the center of mass using <code>colorForTrackingHSV</code> and <code>colorRadius
* </code> as radius (in HSV-color space)
*
* @param hsv the frame of which the center of mass should be calculated off
* @return the center of mass as a point in pixel coordinates (i.e. integer)
*/
public Point calcCenterOfMass(Mat hsv) {
blackWhiteMask = new Mat();
Core.inRange(hsv, lowerBound, upperBound, blackWhiteMask);
dilatedMask = new Mat();
Imgproc.dilate(blackWhiteMask, dilatedMask, new Mat());
contour = new ArrayList<MatOfPoint>();
Mat mHierarchy = new Mat();
Mat tempDilatedMask = dilatedMask.clone();
Imgproc.findContours(
tempDilatedMask, contour, mHierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
boundingRect = Imgproc.boundingRect(findLargestContour(contour));
int centerOfMassX = boundingRect.x + boundingRect.width / 2;
int centerOfMassY = boundingRect.y + boundingRect.height / 2;
Point centerOfMass = new Point(centerOfMassX, centerOfMassY);
trackPath.add(centerOfMass);
return centerOfMass;
}
/**
* 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;
}
/**
* 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);
}
}
}
}
/**
* detection_contours, détecte les contours, les affiches et gères le traitement
* d'authentification
*
* @param inmat : la matrice qui arrive pour la detection de contour
* @param outmat : la matrice qui sort après les comptours
*/
public void detection_contours(Mat inmat, Mat outmat) {
Mat v = new Mat();
Mat vv = outmat.clone();
List<MatOfPoint> contours = new ArrayList(); // Tous les contours
int key; // Plus gros contours
MatOfInt hullI = new MatOfInt();
List<MatOfPoint> hullP = new ArrayList<MatOfPoint>();
Rect r; // Rectangle du plus gros contours
// Trouve tous les contours
Imgproc.findContours(vv, contours, v, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
// Calcul l'indice du plus gros contours
key = findBiggestContour(contours);
// S'il y a au moins un contours et le
if (key != 0) {
Imgproc.drawContours(inmat, contours, key, new Scalar(0, 0, 255));
r = Imgproc.boundingRect(contours.get(key));
Core.rectangle(currentFrame, r.br(), r.tl(), new Scalar(0, 255, 0), 1);
}
// Calcul les points convexes de la main
Imgproc.convexHull(contours.get(key), hullI, false);
// S'il y a des points de convexion
if (hullI != null) {
// Reinitialise les points de convexion
hullP.clear();
// On calcule le nombres de points de convexion
for (int i = 0; contours.size() >= i; i++) hullP.add(new MatOfPoint());
int[] cId = hullI.toArray();
// On récupère dans un tableau de points, les points du contours
Point[] contourPts = contours.get(key).toArray();
// Réinitialisation des points de recherche dans les tableau
int findRectA = 0;
int findRectB = 0;
int findRectC = 0;
int findRectD = 0;
// Pour chaque point de convexion
for (int i = 0; i < cId.length; i++) {
// Dessin du point de convexion sur la matrice
Core.circle(inmat, contourPts[cId[i]], 2, new Scalar(241, 247, 45), -3);
// Si le point de convexion se trouve dans un des carrés
// on incrémente le compteur associé
if (isInRectangle(rectA, contourPts[cId[i]])) findRectA++;
else if (isInRectangle(rectB, contourPts[cId[i]])) findRectB++;
else if (isInRectangle(rectC, contourPts[cId[i]])) findRectC++;
else if (isInRectangle(rectD, contourPts[cId[i]])) findRectD++;
}
// Si on a trouvé la main dans le rectangle A
if (findRectA >= 5) {
if (cptRect == 0) {
numeroRect[cptRect] = 1;
cptRect++;
System.out.println("Haut gauche");
} else {
if (numeroRect[cptRect - 1] != 1) {
numeroRect[cptRect] = 1;
if (cptRect == 3) cptRect = 0;
else cptRect++;
System.out.println("Haut gauche");
}
}
}
// Si on a trouvé la main dans le rectangle B
if (findRectB >= 5) {
if (cptRect == 0) {
numeroRect[cptRect] = 2;
cptRect++;
System.out.println("Bas gauche");
} else {
if (numeroRect[cptRect - 1] != 2) {
numeroRect[cptRect] = 2;
if (cptRect == 3) cptRect = 0;
else cptRect++;
System.out.println("Bas gauche");
}
}
}
// Si on a trouvé la main dans le rectangle C
if (findRectC >= 5) {
if (cptRect == 0) {
numeroRect[cptRect] = 3;
if (cptRect == 3) cptRect = 0;
else cptRect++;
System.out.println("Haut droite");
} else {
if (numeroRect[cptRect - 1] != 3) {
numeroRect[cptRect] = 3;
if (cptRect == 3) cptRect = 0;
else cptRect++;
System.out.println("Haut droite");
}
}
}
// Si on a trouvé la main dans le rectangle D
if (findRectD >= 5) {
if (cptRect == 0) {
numeroRect[cptRect] = 4;
cptRect++;
System.out.println("Bas droite");
} else {
if (numeroRect[cptRect - 1] != 4) {
numeroRect[cptRect] = 4;
if (cptRect == 3) cptRect = 0;
else cptRect++;
System.out.println("Bas droite");
}
}
}
// Si on a sélectionné 3 fenètres et que cela correspond au mot de passe
// MOT DE PASSE : Haut Gauche - Bas Droite - Bas Gauche
if (cptRect == 3) {
if ((numeroRect[0] == 1) && (numeroRect[1] == 4) && (numeroRect[2] == 2))
this.jTextField2.setText("Authenticated");
// Réinitilisation du compteur
cptRect = 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;
}
}*/
}
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;
}
public void processImage(Mat imageToProcess) {
try {
final Mat processedImage = imageToProcess.clone();
// red
final Mat redUpper = new Mat();
final Mat redLower = new Mat();
Core.inRange(processedImage, new Scalar(170, 100, 20), new Scalar(180, 255, 255), redUpper);
Core.inRange(processedImage, new Scalar(0, 100, 20), new Scalar(20, 255, 255), redLower);
Core.bitwise_or(redLower, redUpper, processedImage);
// refining the binary image
Imgproc.erode(processedImage, processedImage, new Mat(), new Point(-1, -1), 1);
Imgproc.dilate(processedImage, processedImage, new Mat(), new Point(-1, -1), 0);
// create a clone for the processedImage to be used in finding contours
final Mat clone = processedImage.clone();
Imgproc.cvtColor(processedImage, processedImage, Imgproc.COLOR_GRAY2RGB);
// finds list of contours and draw the biggest on the processedImage
final Scalar color1 = new Scalar(0, 0, 255);
final Scalar color2 = new Scalar(255, 255, 0);
final Scalar color3 = new Scalar(255, 255, 255);
final List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(
clone, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_NONE);
final List<MatOfPoint> contour = new ArrayList<MatOfPoint>(1);
double maxArea = 0.0;
for (int index = 0; index < contours.size(); index++) {
double area = Imgproc.contourArea(contours.get(index));
if (area > maxArea && area > 25 && Imgproc.boundingRect(contours.get(index)).y > 40) {
maxArea = area;
contour.add(0, contours.get(index));
}
}
// finds bounding Rectangle and draws contours
Rect boundingRect = new Rect();
if (contour.size() > 0) {
Imgproc.drawContours(processedImage, contour, -2, color1);
boundingRect = Imgproc.boundingRect(contour.get(0));
final double x = boundingRect.x;
final double y = boundingRect.y;
final double width = boundingRect.width;
final double height = boundingRect.height;
Core.rectangle(processedImage, new Point(x, y), new Point(x + width, y + height), color3);
}
// finding bounding Circle and draws it
final Point center = new Point();
final float[] radius = new float[1];
if (contour.size() > 0) {
final MatOfPoint2f contour2f = new MatOfPoint2f(contour.get(0).toArray());
Imgproc.minEnclosingCircle(contour2f, center, radius);
Core.circle(processedImage, center, (int) radius[0], color2);
}
final BallStruct redBallStruct = new BallStruct(boundingRect, center, (double) radius[0]);
final BallTargeting ballTargeting = new BallTargeting(redBallStruct);
synchronized (this) {
distanceToRed = ballTargeting.getDistance();
angleToRedInDegrees = ballTargeting.getAngle() * (180 / Math.PI);
this.processedImage = processedImage;
}
} catch (Exception e) {
}
}
public MatOfPoint getContourOfBestMatch() {
if (matches == null) return null;
Mat threshold = new Mat(imgGray.size(), imgGray.type());
Imgproc.threshold(imgGray, threshold, 70, 255, Imgproc.THRESH_TOZERO);
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(
threshold, contours, new Mat(), Imgproc.RETR_CCOMP, Imgproc.CHAIN_APPROX_NONE);
// HashMap<Integer,MatOfPoint> coordinates = computeCoord(contours,)
if (contours.size() == 0) return null;
List<DMatch> matchList = matches.toList();
List<KeyPoint> keyPointList = keyPointImg.toList();
HashMap<Integer, Double> contourDensityMap = new HashMap<Integer, Double>();
Log.i("getContourBestMatch::", "contour size::" + contours.size());
for (int idx = 0; idx < contours.size(); idx++) {
MatOfPoint2f ctr2f = new MatOfPoint2f(contours.get(idx).toArray());
// double contourarea = Imgproc.contourArea(contours.get(idx));
double contourarea = contours.get(idx).rows();
if (contourarea < 50) continue;
Rect r = Imgproc.boundingRect(contours.get(idx));
double count = 0;
// Log.i("contour area","contour area is::"+contourarea);
for (DMatch match : matchList) {
Point q = keyPointList.get(match.queryIdx).pt;
if (q.x >= r.x && q.x <= (r.x + r.width) && q.y >= r.y && q.y <= (r.y + r.height)) count++;
//
// if(Imgproc.pointPolygonTest(ctr2f,keyPointList.get(match.queryIdx).pt,true)>0){
// if(null ==contourDensityMap.get(idx))
// contourDensityMap.put(idx,1.0);
//
// else{
// contourDensityMap.put(idx,((Double)contourDensityMap.get(idx))+1);
// }
//
// }
}
// if(contourDensityMap.containsKey(idx)) {
//
// Log.i("contourPoint","idx::"+idx+"count::"+contourDensityMap.get(idx)+"contour
// area::"+contourarea);
// contourDensityMap.put(idx, contourDensityMap.get(idx) / contourarea);
// }
if (count != 0) {
contourDensityMap.put(idx, count / contourarea);
}
}
Log.i("MarkerTracker", "contour density size::" + contourDensityMap.size());
Map.Entry<Integer, Double> maxEntry = null;
for (Map.Entry<Integer, Double> entry : contourDensityMap.entrySet()) {
Log.i("contourDensityMap", "Entry value::" + entry.getValue());
if (maxEntry == null || entry.getValue().compareTo(maxEntry.getValue()) > 0) {
maxEntry = entry;
}
}
Log.i("maxEntry::", "" + (maxEntry == null ? null : maxEntry.getKey()));
// return contours;
return contours.get(maxEntry != null ? maxEntry.getKey() : 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);
}