public boolean hasChanges(Mat current) {
int PIXEL_DIFF_THRESHOLD = 5;
int IMAGE_DIFF_THRESHOLD = 5;
Mat bg = new Mat();
Mat cg = new Mat();
Mat diff = new Mat();
Mat tdiff = new Mat();
Imgproc.cvtColor(base, bg, Imgproc.COLOR_BGR2GRAY);
Imgproc.cvtColor(current, cg, Imgproc.COLOR_BGR2GRAY);
Core.absdiff(bg, cg, diff);
Imgproc.threshold(diff, tdiff, PIXEL_DIFF_THRESHOLD, 0.0, Imgproc.THRESH_TOZERO);
if (Core.countNonZero(tdiff) <= IMAGE_DIFF_THRESHOLD) {
return false;
}
Imgproc.threshold(diff, diff, PIXEL_DIFF_THRESHOLD, 255, Imgproc.THRESH_BINARY);
Imgproc.dilate(diff, diff, new Mat());
Mat se = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(5, 5));
Imgproc.morphologyEx(diff, diff, Imgproc.MORPH_CLOSE, se);
List<MatOfPoint> points = new ArrayList<MatOfPoint>();
Mat contours = new Mat();
Imgproc.findContours(diff, points, contours, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
int n = 0;
for (Mat pm : points) {
log(lvl, "(%d) %s", n++, pm);
printMatI(pm);
}
log(lvl, "contours: %s", contours);
printMatI(contours);
return true;
}
public Mat convertImageToBlackWhite(Mat imageMat, boolean applyGaussBlur) {
Mat imageCloneMat = imageMat.clone();
if (applyGaussBlur) {
Imgproc.GaussianBlur(imageCloneMat, imageCloneMat, new Size(3, 3), 0, 0);
}
double thresh =
Imgproc.threshold(
imageCloneMat, imageCloneMat, 0, 255, Imgproc.THRESH_BINARY | Imgproc.THRESH_OTSU);
Imgproc.threshold(imageCloneMat, imageCloneMat, thresh, 255, Imgproc.THRESH_BINARY_INV);
return (imageCloneMat);
}
public static Mat warp(Mat inputMat, Mat startM, int factor) {
int resultWidth = 400 * factor;
int resultHeight = 240 * factor;
Mat outputMat = new Mat(resultWidth, resultHeight, CvType.CV_8UC4);
Point ocvPOut1 = new Point(0, 0);
Point ocvPOut2 = new Point(0, resultHeight);
Point ocvPOut3 = new Point(resultWidth, resultHeight);
Point ocvPOut4 = new Point(resultWidth, 0);
List<Point> dest = new ArrayList<Point>();
dest.add(ocvPOut1);
dest.add(ocvPOut2);
dest.add(ocvPOut3);
dest.add(ocvPOut4);
Mat endM = Converters.vector_Point2f_to_Mat(dest);
Mat perspectiveTransform = Imgproc.getPerspectiveTransform(startM, endM);
Imgproc.warpPerspective(
inputMat,
outputMat,
perspectiveTransform,
new Size(resultWidth, resultHeight),
Imgproc.INTER_AREA);
Imgproc.GaussianBlur(outputMat, outputMat, new org.opencv.core.Size(5, 5), 5);
Imgproc.resize(outputMat, outputMat, new Size(resultWidth / factor, resultHeight / factor));
Imgproc.threshold(outputMat, outputMat, 127, 255, Imgproc.THRESH_TOZERO);
return outputMat;
}
/**
* Generates a mask of all resistors present in the given Mat. Also displays this mask in the
* Bottom Left frame of the GUI.
*
* @param imgCap The Mat image to generate the mask for
* @param type The threshold operation type
* @return The mask as a Mat
*/
private Mat generateResistorMask(Mat imgCap, int type) {
Mat imgHSV = new Mat();
Mat satImg = new Mat();
// convert the input image from BGR to HSV
Imgproc.cvtColor(imgCap, imgHSV, Imgproc.COLOR_BGR2HSV);
ArrayList<Mat> channels = new ArrayList<Mat>();
Core.split(imgHSV, channels);
// extract the saturation channel
satImg = channels.get(1);
// remove the background and the resistor leads (combined with previous blurring)
// thresh ~86
Imgproc.threshold(satImg, satImg, RESISTOR_MASK_THRESHOLD, 255, type);
paintBL(satImg);
return satImg;
}
/**
* @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);
}
}
}
}
@Override
public void run() {
// Initialisation
cptRect = 0;
initialiseRectangle();
if (video.isOpened()) {
while (begin == true) {
// On récupère l'image de la CaptureVideo
video.retrieve(frameaux);
// On modifie les dimensions de la frame
Imgproc.resize(frameaux, frame, frame.size());
// On copie
frame.copyTo(currentFrame);
if (jCheckBoxMotionDetection.isSelected()) {
if (firstFrame) {
frame.copyTo(lastFrame);
firstFrame = false;
continue;
}
// Soustraction de currentFrame par rapport à la dernière
Core.subtract(currentFrame, lastFrame, processedFrame);
// Filtre en niveau de gris
Imgproc.cvtColor(processedFrame, processedFrame, Imgproc.COLOR_RGB2GRAY);
// Filtre threshold + récupération du Jslider
int threshold = jSliderThreshold.getValue();
Imgproc.threshold(
processedFrame, processedFrame, threshold, 255, Imgproc.THRESH_BINARY);
// Detecte les contours et check dans les
detection_contours(currentFrame, processedFrame);
}
// Dessine les rectangles d'authentifications
drawRectangle();
currentFrame.copyTo(processedFrame);
// Encodage de la frame en MatOfByte
Highgui.imencode(".jpg", processedFrame, matOfByte);
byte[] byteArray = matOfByte.toArray();
// Affichage de l'image
try {
in = new ByteArrayInputStream(byteArray);
bufImage = ImageIO.read(in);
image.updateImage(bufImage);
} catch (Exception ex) {
ex.printStackTrace();
}
try {
Thread.sleep(50);
} catch (Exception ex) {
ex.printStackTrace();
}
}
}
}
/** new algo */
public static String findTips(Mat image) {
Mat binary = new Mat();
// Convert to B&W image
Imgproc.threshold(image, binary, 0, 255, Imgproc.THRESH_BINARY);
// Convert to binary image, 1 channel
Imgproc.cvtColor(binary, binary, Imgproc.COLOR_RGB2GRAY);
boolean flag_bg = false;
boolean handInQuarterOfImg = false;
int count_finger = 0;
int start = -1;
int end = -1;
int tester = 0; // test variable CAN BE REMOVED
double startPercent = 0, endPercent = 0;
int leftHeight = -1;
int firstHandPixel = -1;
int lastHandPixel = -1;
int KV_midFinger = -1;
int KV_indxFinger = -1;
double pixel[];
for (int i = 0; i < binary.cols(); i++) {
pixel = binary.get((int) (binary.rows() * 0.23), i);
if (pixel[0] != 0.0) {
if (firstHandPixel == -1) firstHandPixel = i;
if (i < image.cols() / 4) handInQuarterOfImg = true;
lastHandPixel = i;
leftHeight = i;
}
if (pixel[0] != 0.0) {
if (flag_bg == false) { // flag_bg is false
count_finger++;
flag_bg = true;
start = i;
}
end = i;
} else {
if (count_finger == 1) KV_midFinger = end;
else if (count_finger == 2) KV_indxFinger = start;
flag_bg = false;
if (tester != count_finger) { // remove this line -- just for
// testing
startPercent = ((double) start / (double) binary.cols()) * 100;
endPercent = ((double) end / (double) binary.cols()) * 100;
}
tester = count_finger; // remove this line -- just for testing
}
}
if (count_finger == 3) {
if (endPercent > 80.0) {
return "W";
} else {
return "F";
}
} else if (count_finger == 4) {
return "B";
} else if (count_finger == 1) {
if (endPercent > 70.0)
if (handInQuarterOfImg) return "B";
else {
int result = identify_R_U(binary);
switch (result) {
case 1:
return "R";
case 2:
return "U";
default:
return " ";
// return "RU";
}
}
else {
if ((float) (lastHandPixel - firstHandPixel) / image.cols() > 0.35) return "F";
else {
image = Filter.furtherClean(image);
Mat binary2 = new Mat();
// Convert to B&W image
Imgproc.threshold(image, binary2, 0, 255, Imgproc.THRESH_BINARY);
// Convert to binary image, 1 channel
Imgproc.cvtColor(binary2, binary2, Imgproc.COLOR_RGB2GRAY);
flag_bg = false;
int countHandArea = 0;
for (int i = 0; i < binary2.rows(); i++) {
pixel = binary2.get(i, (int) (binary2.cols() * 0.70));
if (pixel[0] != 0.0) {
if (!flag_bg) {
flag_bg = true;
countHandArea++;
}
} else flag_bg = false;
}
if (countHandArea == 1) {
if (checkAngleL(binary)) return "L";
else {
int result = identify_R_U(binary);
switch (result) {
case 1:
return "R";
case 2:
return "U";
default:
return " ";
}
}
} else if (countHandArea == 2) return "D";
else return " ";
}
}
} else if (count_finger == 2) {
// int result = identify_K_V(rgb, binary, new Point(KV_midFinger,
// (int) (binary.rows() * 0.23)), new Point(KV_indxFinger,
// (int) (binary.rows() * 0.23)));
int startX = (int) KV_midFinger;
int startY = (int) (binary.rows() * 0.23);
int lastDir = 1; // 0 up; 1 down
int currDir = 1;
int ctr = 1;
Point KV_PtsArray[] = new Point[3];
KV_PtsArray[0] = new Point(startX, startY);
// Core.circle(rgb,
// new Point(UL.x + startX, UL.y + startY), 5,
// new Scalar(0, 0, 255));
// double pixel[];
Log.i("START", "" + startX);
Log.i("END", "" + startY);
for (int i = startX; i < KV_indxFinger; i++) {
for (int k = (int) (binary.rows() * 0.23); k < binary.rows(); k++) {
pixel = binary.get(k, i + 1);
Log.i("CHECK1", "" + binary.rows());
Log.i("CHECK2", "" + binary.rows() * 0.23);
Log.i("CHECK3", "" + (int) (binary.rows() * 0.23));
Log.i("CHECK4", "" + pixel[0]);
if (pixel[0] != 0.0) {
// Plots the edges from hullPoint[0] to hullPoint[1]
// Core.circle(rgb, new Point(UL.x + startX + 1,
// UL.y
// + k), 5, new Scalar(0, 255, 0));
if (k > startY) currDir = 1;
else if (k < startY) currDir = 0;
if (currDir != lastDir && ctr < 3) {
// Plots 3 significant pts in K and V
// Core.circle(rgb,
// new Point(UL.x + i + 1, UL.y + k), 5,
// new Scalar(0, 0, 255));
KV_PtsArray[ctr] = new Point(i + 1, k);
ctr++;
}
lastDir = currDir;
// startX = startX + 1;
startY = k;
break;
}
}
if (ctr < 3 && i + 1 == (int) KV_indxFinger) {
// Core.circle(rgb, new Point(UL.x + startX, UL.y + startY),
// 5,
// new Scalar(0, 0, 255));
KV_PtsArray[ctr] = new Point(i, startY);
ctr++;
}
if (ctr == 3) break;
}
if (ctr == 3) {
if (KV_PtsArray[0].y == KV_PtsArray[2].y) return "V"; // V
else return "K"; // K
} else return " ";
}
return Integer.toString(count_finger);
}
public static void main(String[] args) {
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
// Mat mat = Mat.eye( 3, 3, CvType.CV_8UC1 );
// System.out.println( "mat = " + mat.dump() );
Sample n = new Sample();
// n.templateMatching();
// put text in image
// Mat data= Highgui.imread("images/erosion.jpg");
// Core.putText(data, "Sample", new Point(50,80), Core.FONT_HERSHEY_SIMPLEX, 1, new
// Scalar(0,0,0),2);
//
// Highgui.imwrite("images/erosion2.jpg", data);
// getting dct of an image
String path = "images/croppedfeature/go (20).jpg";
path = "images/wordseg/img1.png";
Mat image = Highgui.imread(path, Highgui.IMREAD_GRAYSCALE);
ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.threshold(image, image, 0, 255, Imgproc.THRESH_OTSU);
Imgproc.threshold(image, image, 220, 128, Imgproc.THRESH_BINARY_INV);
Mat newImg = new Mat(45, 100, image.type());
newImg.setTo(new Scalar(0));
n.copyMat(image, newImg);
int vgap = 25;
int hgap = 45 / 3;
Moments m = Imgproc.moments(image, false);
Mat hu = new Mat();
Imgproc.HuMoments(m, hu);
System.out.println(hu.dump());
// //divide the mat into 12 parts then get the features of each part
// int count=1;
// for(int j=0; j<45; j+=hgap){
// for(int i=0;i<100;i+=vgap){
// Mat result = newImg.submat(j, j+hgap, i, i+vgap);
//
//
// Moments m= Imgproc.moments(result, false);
// double m01= m.get_m01();
// double m00= m.get_m00();
// double m10 = m.get_m10();
// int x= m00!=0? (int)(m10/m00):0;
// int y= m00!=0? (int)(m01/m00):0;
// Mat hu= new Mat();
// Imgproc.HuMoments(m, hu);
// System.out.println(hu.dump());
// System.out.println(count+" :"+x+" and "+y);
// Imgproc.threshold(result, result, 0,254, Imgproc.THRESH_BINARY_INV);
// Highgui.imwrite("images/submat/"+count+".jpg", result);
// count++;
//
// }
// }
//
// for(int i=vgap;i<100;i+=vgap){
// Point pt1= new Point(i, 0);
// Point pt2= new Point(i, 99);
// Core.line(newImg, pt1, pt2, new Scalar(0,0,0));
// }
// for(int i=hgap;i<45;i+=hgap){
// Point pt1= new Point(0, i);
// Point pt2= new Point(99, i);
// Core.line(newImg, pt1, pt2, new Scalar(0,0,0));
// }
// Highgui.imwrite("images/submat/copyto.jpg", newImg);
}
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 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 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);
}