private static Bitmap canny(Bitmap image) {
// convert image to matrix
Mat Mat1 = new Mat(image.getWidth(), image.getHeight(), CvType.CV_32FC1);
Utils.bitmapToMat(image, Mat1);
// create temporary matrix2
Mat Mat2 = new Mat(image.getWidth(), image.getHeight(), CvType.CV_32FC1);
// convert image to grayscale
Imgproc.cvtColor(Mat1, Mat2, Imgproc.COLOR_BGR2GRAY);
// doing a gaussian blur prevents getting a lot of false hits
Imgproc.GaussianBlur(Mat2, Mat1, new Size(3, 3), 2, 2); // ?
// now apply canny function
int param_threshold1 = 25; // manually defined
int param_threshold2 = param_threshold1 * 3; // Cannys recommendation
Imgproc.Canny(Mat1, Mat2, param_threshold1, param_threshold2);
// ?
Imgproc.cvtColor(Mat2, Mat1, Imgproc.COLOR_GRAY2BGRA, 4);
// convert matrix to output bitmap
Bitmap output = Bitmap.createBitmap(image.getWidth(), image.getHeight(), Bitmap.Config.RGB_565);
Utils.matToBitmap(Mat1, output);
return output;
}
/**
* 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;
}
/**
* @param image
* @param size
* @return Mat
*/
public static Mat cannyDetection(Mat image, int size) {
Mat grayImage = new Mat();
Mat detectedEdges = new Mat();
// convert to grayscale
Imgproc.cvtColor(image, grayImage, Imgproc.COLOR_BGR2GRAY);
// reduce noise with a 3x3 kernel
Imgproc.blur(grayImage, detectedEdges, new Size(3, 3));
// canny detector, with ratio of lower:upper threshold of 3:1
Imgproc.Canny(detectedEdges, detectedEdges, size, size / 3, 7, false);
return detectedEdges;
}
/**
* 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 void processWithContours(Mat in, Mat out) {
int playSquares = 32; // number of playable game board squares
// 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() / 10; // 8 playable, 2 capture
int hOffset = hsegment * 2; // offset for playable board
int vOffset = vsegment + 40;
// For angle of camera
int dx = 80;
int ddx = 0;
hsegment -= 16;
int dy = 20;
vsegment -= 24;
int ddy = 0;
// 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 2nd square from left
{
if (rowNum >= 5) dx -= 3;
hOffset = hsegment * 2 + dx;
} else // playable squares start on immediate left
{
if (rowNum >= 5) dx -= 3;
hOffset = hsegment + dx;
}
if (rowNum == 0) ddy = 5;
if (rowNum == 4) if (count == 6) ddx = 10;
if (rowNum == 5) {
if (count == 0) ddx = -6;
else if (count == 2) ddx = 6;
else if (count == 4) ddx = 12;
else if (count == 6) ddx = 20;
}
if (rowNum == 6) {
if (count == 0) ddx = 0;
else if (count == 2) ddx = 16;
else if (count == 4) ddx = 32;
else if (count == 6) ddx = 40;
}
if (rowNum == 7) {
if (count == 0) ddx = 6;
else if (count == 2) ddx = 24;
else if (count == 4) ddx = 40;
else ddx = 52;
}
// find where roi should be
// System.out.println("" + vOffset);
Point p1 =
new Point(
hOffset + count * hsegment + ddx + 5,
vOffset + rowNum * vsegment - dy - 5 - ddy); // top left point of rectangle (x,y)
Point p2 =
new Point(
hOffset + (count + 1) * hsegment + ddx - 5,
vOffset
+ (rowNum + 1) * vsegment
- dy
- 5
- ddy); // bottom right point of rectangle (x,y)
// create rectangle that is board square
Rect bound = new Rect(p1, p2);
Mat roi;
char color;
if (i == 0) {
// frame only includes rectangle
roi = new Mat(in, bound);
// get the color
color = identifyColor(roi);
// copy input image to output image
in.copyTo(out);
} else {
// frame only includes rectangle
roi = new Mat(out, bound);
// get the color
color = identifyColor(roi);
}
Imgproc.cvtColor(roi, roi, Imgproc.COLOR_BGR2GRAY); // change to single color
Mat canny = new Mat();
Imgproc.Canny(roi, canny, 20, 40); // 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
System.out.println(++test + "\t" + contours.size());
if (contours.size() > 3) // or error value for color is below 1
{
switch (color) {
case COLOR_BLUE:
// Imgproc.rectangle(out, p1, p2, new Scalar(255, 0, 0), 2);
Core.rectangle(out, p1, p2, new Scalar(255, 0, 0), 2);
board[i] = CheckersBoard.BLACK; // end user's piece
break;
case COLOR_ORANGE:
// Imgproc.rectangle(out, p1, p2, new Scalar(0, 128, 255), 2);
Core.rectangle(out, p1, p2, new Scalar(0, 128, 255), 2);
board[i] = CheckersBoard.WHITE; // system's piece
break;
case COLOR_WHITE:
// Imgproc.rectangle(out, p1, p2, new Scalar(255, 255, 255), 2);
Core.rectangle(out, p1, p2, new Scalar(255, 255, 255), 2);
board[i] = CheckersBoard.EMPTY;
break;
case COLOR_BLACK: // this is black
// Imgproc.rectangle(out, p1, p2, new Scalar(0, 0, 0), 2);
Core.rectangle(
out,
p1,
p2,
new Scalar(0, 0, 0),
2); // maybe add 8, 0 as line type and fractional bits
board[i] = CheckersBoard.EMPTY;
break;
}
}
System.out.println("in color switch " + board[i]);
count += 2;
if (count == 8) {
parity = ++parity % 2; // change odd or even
count = 0;
rowNum++;
hsegment += 2;
dx -= 10;
dy += 10;
vsegment += 3;
ddy = 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;
}
}*/
}
@Override
protected Bitmap processFrame(VideoCapture capture) {
Time[] measureTime = new Time[9];
String[] compDescStrings = {
"Total processFrame",
"Grab a new frame",
"MatToBitmap",
"Publish cameraInfo",
"Create ImageMsg",
"Compress image",
"Transfer to Stream",
"Image.SetData",
"Publish Image",
"Total econds per frame"
};
String[] rawDescStrings = {
"Total processFrame",
"Grab a new frame",
"MatToBitmap",
"Publish cameraInfo",
"Create ImageMsg",
"Pixel to buffer",
"Transfer to Stream",
"Image.SetData",
"Publish Image",
"Total seconds per frame"
};
measureTime[0] = connectedNode.getCurrentTime();
switch (MainActivity.viewMode) {
case MainActivity.VIEW_MODE_GRAY:
// capture.retrieve(mGray, Highgui.CV_CAP_ANDROID_GREY_FRAME);
capture.retrieve(mRgba, Highgui.CV_CAP_ANDROID_GREY_FRAME);
// Imgproc.cvtColor(mGray, mRgba, Imgproc.COLOR_GRAY2RGBA, 4);
break;
case MainActivity.VIEW_MODE_RGBA:
capture.retrieve(mRgba, Highgui.CV_CAP_ANDROID_COLOR_FRAME_RGBA);
// Core.putText(mRgba, "OpenCV + Android", new Point(10, 100), 3, 2, new
// Scalar(255, 0, 0, 255), 3);
break;
case MainActivity.VIEW_MODE_CANNY:
capture.retrieve(mGray, Highgui.CV_CAP_ANDROID_GREY_FRAME);
Imgproc.Canny(mGray, mIntermediateMat, 80, 100);
Imgproc.cvtColor(mIntermediateMat, mRgba, Imgproc.COLOR_GRAY2BGRA, 4);
break;
}
Time currentTime = connectedNode.getCurrentTime();
measureTime[1] = connectedNode.getCurrentTime();
if (bmp == null) bmp = Bitmap.createBitmap(mRgba.cols(), mRgba.rows(), Bitmap.Config.ARGB_8888);
if (MainActivity.imageCompression == MainActivity.IMAGE_TRANSPORT_COMPRESSION_NONE
&& bb == null) {
Log.i(TAG, "Buffer 1");
bb = ByteBuffer.allocate(bmp.getRowBytes() * bmp.getHeight());
Log.i(TAG, "Buffer 2");
bb.clear();
Log.i(TAG, "Buffer 3");
}
try {
Utils.matToBitmap(mRgba, bmp);
measureTime[2] = connectedNode.getCurrentTime();
cameraInfo = cameraInfoPublisher.newMessage();
cameraInfo.getHeader().setFrameId("camera");
cameraInfo.getHeader().setStamp(currentTime);
cameraInfo.setWidth(640);
cameraInfo.setHeight(480);
cameraInfoPublisher.publish(cameraInfo);
measureTime[3] = connectedNode.getCurrentTime();
if (MainActivity.imageCompression >= MainActivity.IMAGE_TRANSPORT_COMPRESSION_PNG) {
// Compressed image
sensor_msgs.CompressedImage image = imagePublisher.newMessage();
if (MainActivity.imageCompression == MainActivity.IMAGE_TRANSPORT_COMPRESSION_PNG)
image.setFormat("png");
else if (MainActivity.imageCompression == MainActivity.IMAGE_TRANSPORT_COMPRESSION_JPEG)
image.setFormat("jpeg");
image.getHeader().setStamp(currentTime);
image.getHeader().setFrameId("camera");
measureTime[4] = connectedNode.getCurrentTime();
ByteArrayOutputStream baos = new ByteArrayOutputStream();
if (MainActivity.imageCompression == MainActivity.IMAGE_TRANSPORT_COMPRESSION_PNG)
bmp.compress(Bitmap.CompressFormat.PNG, 100, baos);
else if (MainActivity.imageCompression == MainActivity.IMAGE_TRANSPORT_COMPRESSION_JPEG)
bmp.compress(Bitmap.CompressFormat.JPEG, MainActivity.imageCompressionQuality, baos);
measureTime[5] = connectedNode.getCurrentTime();
stream.buffer().writeBytes(baos.toByteArray());
measureTime[6] = connectedNode.getCurrentTime();
image.setData(stream.buffer().copy());
measureTime[7] = connectedNode.getCurrentTime();
stream.buffer().clear();
imagePublisher.publish(image);
measureTime[8] = connectedNode.getCurrentTime();
} else {
// Raw image
Log.i(TAG, "Raw image 1");
sensor_msgs.Image rawImage = rawImagePublisher.newMessage();
rawImage.getHeader().setStamp(currentTime);
rawImage.getHeader().setFrameId("camera");
rawImage.setEncoding("rgba8");
rawImage.setWidth(bmp.getWidth());
rawImage.setHeight(bmp.getHeight());
rawImage.setStep(640);
measureTime[4] = connectedNode.getCurrentTime();
Log.i(TAG, "Raw image 2");
bmp.copyPixelsToBuffer(bb);
measureTime[5] = connectedNode.getCurrentTime();
Log.i(TAG, "Raw image 3");
stream.buffer().writeBytes(bb.array());
bb.clear();
measureTime[6] = connectedNode.getCurrentTime();
Log.i(TAG, "Raw image 4");
rawImage.setData(stream.buffer().copy());
stream.buffer().clear();
measureTime[7] = connectedNode.getCurrentTime();
Log.i(TAG, "Raw image 5");
rawImagePublisher.publish(rawImage);
measureTime[8] = connectedNode.getCurrentTime();
Log.i(TAG, "Raw image 6");
}
newTime = connectedNode.getCurrentTime();
stats[9][counter] = (newTime.subtract(oldTime)).nsecs / 1000000.0;
oldTime = newTime;
for (int i = 1; i < 9; i++) {
stats[i][counter] = (measureTime[i].subtract(measureTime[i - 1])).nsecs / 1000000.0;
}
stats[0][counter] = measureTime[8].subtract(measureTime[0]).nsecs / 1000000.0;
counter++;
if (counter == numSamples) {
double[] sts = new double[10];
Arrays.fill(sts, 0.0);
for (int i = 0; i < 10; i++) {
for (int j = 0; j < numSamples; j++) sts[i] += stats[i][j];
sts[i] /= (double) numSamples;
if (MainActivity.imageCompression >= MainActivity.IMAGE_TRANSPORT_COMPRESSION_PNG)
Log.i(TAG, String.format("Mean time for %s:\t\t%4.2fms", compDescStrings[i], sts[i]));
else Log.i(TAG, String.format("Mean time for %s:\t\t%4.2fms", rawDescStrings[i], sts[i]));
}
Log.i(TAG, "\n\n");
counter = 0;
}
return bmp;
} catch (Exception e) {
Log.e(TAG, "Frame conversion and publishing throws an exception: " + e.getMessage());
bmp.recycle();
return null;
}
}
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 Mat onCameraFrame(Mat inputFrame) {
inputFrame.copyTo(mRgba);
switch (ImageManipulationsActivity.viewMode) {
case ImageManipulationsActivity.VIEW_MODE_RGBA:
break;
case ImageManipulationsActivity.VIEW_MODE_HIST:
if ((mSizeRgba == null)
|| (mRgba.cols() != mSizeRgba.width)
|| (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();
int thikness = (int) (mSizeRgba.width / (mHistSizeNum + 10) / 5);
if (thikness > 5) thikness = 5;
int offset = (int) ((mSizeRgba.width - (5 * mHistSizeNum + 4 * 10) * thikness) / 2);
// RGB
for (int c = 0; c < 3; c++) {
Imgproc.calcHist(Arrays.asList(mRgba), mChannels[c], mMat0, mHist, mHistSize, mRanges);
Core.normalize(mHist, mHist, mSizeRgba.height / 2, 0, Core.NORM_INF);
mHist.get(0, 0, mBuff);
for (int h = 0; h < mHistSizeNum; h++) {
mP1.x = mP2.x = offset + (c * (mHistSizeNum + 10) + h) * thikness;
mP1.y = mSizeRgba.height - 1;
mP2.y = mP1.y - 2 - (int) mBuff[h];
Core.line(mRgba, mP1, mP2, mColorsRGB[c], thikness);
}
}
// Value and Hue
Imgproc.cvtColor(mRgba, mIntermediateMat, Imgproc.COLOR_RGB2HSV_FULL);
// Value
Imgproc.calcHist(
Arrays.asList(mIntermediateMat), mChannels[2], mMat0, mHist, mHistSize, mRanges);
Core.normalize(mHist, mHist, mSizeRgba.height / 2, 0, Core.NORM_INF);
mHist.get(0, 0, mBuff);
for (int h = 0; h < mHistSizeNum; h++) {
mP1.x = mP2.x = offset + (3 * (mHistSizeNum + 10) + h) * thikness;
mP1.y = mSizeRgba.height - 1;
mP2.y = mP1.y - 2 - (int) mBuff[h];
Core.line(mRgba, mP1, mP2, mWhilte, thikness);
}
// Hue
Imgproc.calcHist(
Arrays.asList(mIntermediateMat), mChannels[0], mMat0, mHist, mHistSize, mRanges);
Core.normalize(mHist, mHist, mSizeRgba.height / 2, 0, Core.NORM_INF);
mHist.get(0, 0, mBuff);
for (int h = 0; h < mHistSizeNum; h++) {
mP1.x = mP2.x = offset + (4 * (mHistSizeNum + 10) + h) * thikness;
mP1.y = mSizeRgba.height - 1;
mP2.y = mP1.y - 2 - (int) mBuff[h];
Core.line(mRgba, mP1, mP2, mColorsHue[h], thikness);
}
break;
case ImageManipulationsActivity.VIEW_MODE_CANNY:
if ((mRgbaInnerWindow == null)
|| (mGrayInnerWindow == null)
|| (mRgba.cols() != mSizeRgba.width)
|| (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();
Imgproc.Canny(mRgbaInnerWindow, mIntermediateMat, 80, 90);
Imgproc.cvtColor(mIntermediateMat, mRgbaInnerWindow, Imgproc.COLOR_GRAY2BGRA, 4);
break;
case ImageManipulationsActivity.VIEW_MODE_SOBEL:
Imgproc.cvtColor(mRgba, mGray, Imgproc.COLOR_RGBA2GRAY);
if ((mRgbaInnerWindow == null)
|| (mGrayInnerWindow == null)
|| (mRgba.cols() != mSizeRgba.width)
|| (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();
Imgproc.Sobel(mGrayInnerWindow, mIntermediateMat, CvType.CV_8U, 1, 1);
Core.convertScaleAbs(mIntermediateMat, mIntermediateMat, 10, 0);
Imgproc.cvtColor(mIntermediateMat, mRgbaInnerWindow, Imgproc.COLOR_GRAY2BGRA, 4);
break;
case ImageManipulationsActivity.VIEW_MODE_SEPIA:
Core.transform(mRgba, mRgba, mSepiaKernel);
break;
case ImageManipulationsActivity.VIEW_MODE_ZOOM:
if ((mZoomCorner == null)
|| (mZoomWindow == null)
|| (mRgba.cols() != mSizeRgba.width)
|| (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();
Imgproc.resize(mZoomWindow, mZoomCorner, mZoomCorner.size());
Size wsize = mZoomWindow.size();
Core.rectangle(
mZoomWindow,
new Point(1, 1),
new Point(wsize.width - 2, wsize.height - 2),
new Scalar(255, 0, 0, 255),
2);
break;
case ImageManipulationsActivity.VIEW_MODE_PIXELIZE:
if ((mRgbaInnerWindow == null)
|| (mRgba.cols() != mSizeRgba.width)
|| (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();
Imgproc.resize(mRgbaInnerWindow, mIntermediateMat, mSize0, 0.1, 0.1, Imgproc.INTER_NEAREST);
Imgproc.resize(
mIntermediateMat, mRgbaInnerWindow, mSizeRgbaInner, 0., 0., Imgproc.INTER_NEAREST);
break;
case ImageManipulationsActivity.VIEW_MODE_POSTERIZE:
if ((mRgbaInnerWindow == null)
|| (mRgba.cols() != mSizeRgba.width)
|| (mRgba.height() != mSizeRgba.height)) CreateAuxiliaryMats();
/*
Imgproc.cvtColor(mRgbaInnerWindow, mIntermediateMat, Imgproc.COLOR_RGBA2RGB);
Imgproc.pyrMeanShiftFiltering(mIntermediateMat, mIntermediateMat, 5, 50);
Imgproc.cvtColor(mIntermediateMat, mRgbaInnerWindow, Imgproc.COLOR_RGB2RGBA);
*/
Imgproc.Canny(mRgbaInnerWindow, mIntermediateMat, 80, 90);
mRgbaInnerWindow.setTo(new Scalar(0, 0, 0, 255), mIntermediateMat);
Core.convertScaleAbs(mRgbaInnerWindow, mIntermediateMat, 1. / 16, 0);
Core.convertScaleAbs(mIntermediateMat, mRgbaInnerWindow, 16, 0);
break;
}
return mRgba;
}
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;
}
