/**
* Locate rectangles in an image
*
* @param grayImage Grayscale image
* @return Rectangle locations
*/
public RectangleLocationResult locateRectangles(Mat grayImage) {
Mat gray = grayImage.clone();
// Filter out some noise
Filter.downsample(gray, 2);
Filter.upsample(gray, 2);
Mat cacheHierarchy = new Mat();
Mat grayTemp = new Mat();
List<Rectangle> rectangles = new ArrayList<>();
List<Contour> contours = new ArrayList<>();
Imgproc.Canny(gray, grayTemp, 0, THRESHOLD_CANNY, APERTURE_CANNY, true);
Filter.dilate(gray, 2);
List<MatOfPoint> contoursTemp = new ArrayList<>();
// Find contours - the parameters here are very important to compression and retention
Imgproc.findContours(
grayTemp, contoursTemp, cacheHierarchy, Imgproc.CV_RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
// For each contour, test whether the contour is a rectangle
// List<Contour> contours = new ArrayList<>();
MatOfPoint2f approx = new MatOfPoint2f();
for (MatOfPoint co : contoursTemp) {
MatOfPoint2f matOfPoint2f = new MatOfPoint2f(co.toArray());
Contour c = new Contour(co);
// Attempt to fit the contour to the best polygon
Imgproc.approxPolyDP(
matOfPoint2f, approx, c.arcLength(true) * EPLISON_APPROX_TOLERANCE_FACTOR, true);
Contour approxContour = new Contour(approx);
// Make sure the contour is big enough, CLOSED (convex), and has exactly 4 points
if (approx.toArray().length == 4
&& Math.abs(approxContour.area()) > 1000
&& approxContour.isClosed()) {
// TODO contours and rectangles array may not match up, but why would they?
contours.add(approxContour);
// Check each angle to be approximately 90 degrees
double maxCosine = 0;
for (int j = 2; j < 5; j++) {
double cosine =
Math.abs(
MathUtil.angle(
approx.toArray()[j % 4], approx.toArray()[j - 2], approx.toArray()[j - 1]));
maxCosine = Math.max(maxCosine, cosine);
}
if (maxCosine < MAX_COSINE_VALUE) {
// Convert the points to a rectangle instance
rectangles.add(new Rectangle(approx.toArray()));
}
}
}
return new RectangleLocationResult(contours, rectangles);
}
private static Mat findLargestRectangle(Mat original_image) {
Mat imgSource = original_image.clone();
// convert the image to black and white
Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BGR2GRAY);
// convert the image to black and white does (8 bit)
Imgproc.Canny(imgSource, imgSource, 50, 50);
// apply gaussian blur to smoothen lines of dots
Imgproc.GaussianBlur(imgSource, imgSource, new Size(5, 5), 5);
// find the contours
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(
imgSource, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
double maxArea = -1;
MatOfPoint temp_contour = contours.get(0); // the largest is at the
// index 0 for starting
// point
MatOfPoint2f approxCurve = new MatOfPoint2f();
List<MatOfPoint> largest_contours = new ArrayList<MatOfPoint>();
for (int idx = 0; idx < contours.size(); idx++) {
temp_contour = contours.get(idx);
double contourarea = Imgproc.contourArea(temp_contour);
// compare this contour to the previous largest contour found
if (contourarea > maxArea) {
// check if this contour is a square
MatOfPoint2f new_mat = new MatOfPoint2f(temp_contour.toArray());
int contourSize = (int) temp_contour.total();
Imgproc.approxPolyDP(new_mat, approxCurve, contourSize * 0.05, true);
if (approxCurve.total() == 4) {
maxArea = contourarea;
largest_contours.add(temp_contour);
}
}
}
MatOfPoint temp_largest = largest_contours.get(largest_contours.size() - 1);
largest_contours = new ArrayList<MatOfPoint>();
largest_contours.add(temp_largest);
// Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BayerBG2RGB);
Imgproc.drawContours(original_image, largest_contours, -1, new Scalar(0, 255, 0), 10);
// Mat perspectiveTransform = new Mat(3, 3, CvType.CV_32FC1);
// Imgproc.warpPerspective(original_image, imgSource,
// perspectiveTransform, new Size(300,300));
Highgui.imwrite(output, original_image);
// create the new image here using the largest detected square
// Toast.makeText(getApplicationContext(), "Largest Contour: ",
// Toast.LENGTH_LONG).show();
return imgSource;
}
public static Mat getCCH(Mat image) {
ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Mat hierarchy = new Mat();
Imgproc.findContours(
image, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_NONE);
Mat chainHistogram = Mat.zeros(1, 8, CvType.CV_32F);
int n = 0;
MatOfPoint2f approxCurve = new MatOfPoint2f();
for (MatOfPoint contour : contours) {
// get the freeman chain code from the contours
int rows = contour.rows();
// System.out.println("\nrows"+rows+"\n"+contour.dump());
int direction = 7;
Mat prevPoint = contours.get(0).row(0);
n += rows - 1;
for (int i = 1; i < rows; i++) {
// get the current point
double x1 = contour.get(i - 1, 0)[1];
double y1 = contour.get(i - 1, 0)[0];
// get the second point
double x2 = contour.get(i, 0)[1];
double y2 = contour.get(i, 0)[0];
if (x2 == x1 && y2 == y1 + 1) direction = 0;
else if (x2 == x1 - 1 && y2 == y1 + 1) direction = 1;
else if (x2 == x1 - 1 && y2 == y1) direction = 2;
else if (x2 == x1 - 1 && y2 == y1 - 1) direction = 3;
else if (x2 == x1 && y2 == y1 - 1) direction = 4;
else if (x2 == x1 + 1 && y2 == y1 - 1) direction = 5;
else if (x2 == x1 + 1 && y2 == y1) direction = 6;
else if (x2 == x1 + 1 && y2 == y1 + 1) direction = 7;
else System.out.print("err");
double counter = chainHistogram.get(0, direction)[0];
chainHistogram.put(0, direction, ++counter);
System.out.print(direction);
}
}
System.out.println("\n" + chainHistogram.dump());
Scalar alpha = new Scalar(n); // the factor
Core.divide(chainHistogram, alpha, chainHistogram);
System.out.println("\nrows=" + n + " " + chainHistogram.dump());
return chainHistogram;
}
public static Point getFirstPoint(MatOfPoint o) {
Point zero = new Point(0, 0);
Point first = new Point(Double.MAX_VALUE, Double.MAX_VALUE);
double minDist = Double.MAX_VALUE;
for (Point point : o.toList()) {
double dist = Util.euclideanDist(zero, point);
if (dist < minDist) {
first = point;
minDist = dist;
}
}
return first;
}
/**
* Locate ellipses within an image
*
* @param grayImage Grayscale image
* @return Ellipse locations
*/
public EllipseLocationResult locateEllipses(Mat grayImage) {
Mat gray = grayImage.clone();
Filter.downsample(gray, 2);
Filter.upsample(gray, 2);
Imgproc.Canny(gray, gray, 5, 75, 3, true);
Filter.dilate(gray, 2);
Mat cacheHierarchy = new Mat();
List<MatOfPoint> contoursTemp = new ArrayList<>();
// Find contours - the parameters here are very important to compression and retention
Imgproc.findContours(
gray, contoursTemp, cacheHierarchy, Imgproc.CV_RETR_TREE, Imgproc.CHAIN_APPROX_TC89_KCOS);
// List contours
List<Contour> contours = new ArrayList<>();
for (MatOfPoint co : contoursTemp) {
contours.add(new Contour(co));
}
// Find ellipses by finding fit
List<Ellipse> ellipses = new ArrayList<>();
for (MatOfPoint co : contoursTemp) {
contours.add(new Contour(co));
// Contour must have at least 6 points for fitEllipse
if (co.toArray().length < 6) continue;
// Copy MatOfPoint to MatOfPoint2f
MatOfPoint2f matOfPoint2f = new MatOfPoint2f(co.toArray());
// Fit an ellipse to the current contour
Ellipse ellipse = new Ellipse(Imgproc.fitEllipse(matOfPoint2f));
// Draw ellipse
ellipses.add(ellipse);
}
return new EllipseLocationResult(contours, ellipses);
}
public static int identify_R_U(Mat binary) {
// 0: hull points identified < 2
// 1: R
// 2: U
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
List<MatOfPoint> hullPoints = new ArrayList<MatOfPoint>();
List<Point> hullPointList = new ArrayList<Point>();
List<Point> filteredPointList = new ArrayList<Point>();
MatOfPoint hullPointMat = new MatOfPoint();
MatOfInt hull = new MatOfInt();
Mat hierarchy = new Mat();
// Find contour
Imgproc.findContours(
binary, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE);
// Find convex hull
for (int k = 0; k < contours.size(); k++) {
Imgproc.convexHull(contours.get(k), hull);
for (int j = 0; j < hull.toList().size(); j++) {
hullPointList.add(contours.get(k).toList().get(hull.toList().get(j)));
}
hullPointMat.fromList(hullPointList);
hullPoints.add(hullPointMat);
}
// Filter hull points. Only hull points relevant to hull classification
// will remain.
// Also, count the number of filtered hull points in left and right.
for (int l = 0; l < hullPointList.size(); l++) {
if (hullPointList.get(l).y < binary.rows() * 0.25) {
if (l != hullPointList.size() - 1) {
if (Math.hypot(
hullPointList.get(l).x - hullPointList.get(l + 1).x,
hullPointList.get(l).y - hullPointList.get(l + 1).y)
/ binary.cols()
> 0.08) {
filteredPointList.add(hullPointList.get(l));
// Core.circle(rgb,
// new Point(UL.x + hullPointList.get(l).x, UL.y
// + hullPointList.get(l).y), 5,
// new Scalar(0, 255, 0));
}
}
}
}
// Sort points by x axis, increasing
if (filteredPointList.size() > 1) {
if (filteredPointList.get(0).x > filteredPointList.get(1).x) {
Point temp = filteredPointList.get(0);
filteredPointList.set(0, filteredPointList.get(1));
filteredPointList.set(1, temp);
}
if (filteredPointList.get(0).y > filteredPointList.get(1).y) return 1; // R
else return 2; // U
}
return 0;
}
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 Point findLaser(Mat inputFrame) {
Mat mHsv = new Mat();
Imgproc.cvtColor(inputFrame, mHsv, Imgproc.COLOR_RGB2HSV);
// Find laser center
Mat center = new Mat();
Core.inRange(mHsv, new Scalar(0, 0, 250), new Scalar(180, 16, 255), center);
Mat h = new Mat();
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(center, contours, h, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
center.release();
Mat center_mask = Mat.zeros(inputFrame.rows(), inputFrame.cols(), CvType.CV_8U);
if (contours.size() > 0) {
for (int i = 0; i < contours.size(); i++) {
int radius = 10;
// Point[] cont_pos = contours.get(i).toArray();
Moments m = Imgproc.moments(contours.get(i));
Point p = new Point();
p.x = m.get_m10() / m.get_m00();
p.y = m.get_m01() / m.get_m00();
Core.circle(center_mask, p, radius * 2, new Scalar(255), -1);
}
}
// Find halo
Mat ranged = new Mat();
Core.inRange(mHsv, new Scalar(100, 32, 225), new Scalar(150, 255, 255), ranged);
mHsv.release();
// Mat f_frame =ranged.clone();
// Find halo around bright dot
Core.bitwise_and(ranged, center_mask, ranged);
center_mask.release();
// Find biggest resulting contour
for (int i = 1; i < contours.size(); i++) {
contours.get(i).release();
}
contours.clear();
Imgproc.findContours(ranged, contours, h, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
h.release();
ranged.release();
if (contours.size() > 0) {
MatOfPoint biggest_cont = contours.get(0);
double cont_size = Imgproc.contourArea(biggest_cont);
for (int i = 1; i < contours.size(); i++) {
MatOfPoint cur = contours.get(i);
if (Imgproc.contourArea(cur) > cont_size) {
biggest_cont = cur;
cont_size = Imgproc.contourArea(cur);
}
}
Moments m = Imgproc.moments(biggest_cont);
Point p = new Point();
p.x = m.get_m10() / m.get_m00();
p.y = m.get_m01() / m.get_m00();
for (int i = 1; i < contours.size(); i++) {
contours.get(i).release();
}
biggest_cont.release();
return p;
} else {
return null;
}
}
public static void getSquare(Mat imgSource) {
Mat sourceImage = imgSource.clone();
Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BGR2GRAY);
// convert the image to black and white does (8 bit)
Imgproc.Canny(imgSource, imgSource, 50, 50);
// apply gaussian blur to smoothen lines of dots
Imgproc.GaussianBlur(imgSource, imgSource, new org.opencv.core.Size(5, 5), 5);
// find the contours
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
Imgproc.findContours(
imgSource, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
double maxArea = -1;
int maxAreaIdx = -1;
// Log.d("size",Integer.toString(contours.size()));
MatOfPoint temp_contour = contours.get(0); // the largest is at the
// index 0 for starting
// point
MatOfPoint2f approxCurve = new MatOfPoint2f();
MatOfPoint largest_contour = contours.get(0);
// largest_contour.ge
List<MatOfPoint> largest_contours = new ArrayList<MatOfPoint>();
// Imgproc.drawContours(imgSource,contours, -1, new Scalar(0, 255, 0),
// 1);
for (int idx = 0; idx < contours.size(); idx++) {
temp_contour = contours.get(idx);
double contourarea = Imgproc.contourArea(temp_contour);
// compare this contour to the previous largest contour found
if (contourarea > maxArea) {
// check if this contour is a square
MatOfPoint2f new_mat = new MatOfPoint2f(temp_contour.toArray());
int contourSize = (int) temp_contour.total();
MatOfPoint2f approxCurve_temp = new MatOfPoint2f();
Imgproc.approxPolyDP(new_mat, approxCurve_temp, contourSize * 0.05, true);
if (approxCurve_temp.total() == 4) {
maxArea = contourarea;
maxAreaIdx = idx;
approxCurve = approxCurve_temp;
largest_contour = temp_contour;
}
}
}
Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BayerBG2RGB);
double[] temp_double;
temp_double = approxCurve.get(0, 0);
Point p1 = new Point(temp_double[0], temp_double[1]);
// Core.circle(imgSource,p1,55,new Scalar(0,0,255));
// Imgproc.warpAffine(sourceImage, dummy, rotImage,sourceImage.size());
temp_double = approxCurve.get(1, 0);
Point p2 = new Point(temp_double[0], temp_double[1]);
// Core.circle(imgSource,p2,150,new Scalar(255,255,255));
temp_double = approxCurve.get(2, 0);
Point p3 = new Point(temp_double[0], temp_double[1]);
// Core.circle(imgSource,p3,200,new Scalar(255,0,0));
temp_double = approxCurve.get(3, 0);
Point p4 = new Point(temp_double[0], temp_double[1]);
// Core.circle(imgSource,p4,100,new Scalar(0,0,255));
List<Point> source = getCorners(p1, p2, p3, p4);
for (Point p : source) {
// System.out.println(p);
}
Mat startM = Converters.vector_Point2f_to_Mat(source);
// Imgproc.cvtColor(sourceImage, sourceImage, Imgproc.COLOR_BGR2GRAY);
Mat result = warp(sourceImage, startM, 5);
// result = warp(result,result,1);
// Imgproc.cvtColor(result, result, Imgproc.COLOR_BGR2GRAY);
Highgui.imwrite(output, result);
// System.out.println("Done");
// return result;
}