Comment effectuer le recadrage Automatique de document Reconnaître des images à l'aide de la caméra?

Ici est exactement la même démos que vous voulez atteindre

https://github.com/Aniruddha-Tapas/Document-Scanner (A dispositif d'auto-détection)

https://github.com/jhansireddy/AndroidScannerDemo

Je sais que je suis trop en retard pour répondre, mais il pourrait être utile à quelqu'un.

Essayez le code suivant.

@Override
protected void onDraw(Canvas canvas) {

  super.onDraw(canvas);
  path = new Path();

  path.moveTo(x1, y1);        //this should set the start point right

  //path.lineTo(x1, y1);    <-- this line should be drawn at the end of     course,sorry
  path.lineTo(x2, y2);
  path.lineTo(x3, y3);
  path.lineTo(x4, y4);
  path.lineTo(x1, y1); 
  canvas.drawPath(path, currentPaint);

}

Passer votre image mat dans cette méthode:

       void findSquares(Mat image, List<MatOfPoint> squares) {
int N = 10;
squares.clear();
Mat smallerImg = new Mat(new Size(image.width() / 2, image.height() / 2), image.type());
Mat gray = new Mat(image.size(), image.type());
Mat gray0 = new Mat(image.size(), CvType.CV_8U);
//down-scale and upscale the image to filter out the noise
Imgproc.pyrDown(image, smallerImg, smallerImg.size());
Imgproc.pyrUp(smallerImg, image, image.size());
//find squares in every color plane of the image
Outer:
for (int c = 0; c < 3; c++) {
extractChannel(image, gray, c);
//try several threshold levels
Inner:
for (int l = 1; l < N; l++) {
Imgproc.threshold(gray, gray0, (l + 1) * 255 / N, 255, Imgproc.THRESH_BINARY);
List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
//find contours and store them all as a list
Imgproc.findContours(gray0, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
MatOfPoint approx = new MatOfPoint();
//test each contour
for (int i = 0; i < contours.size(); i++) {
approx = approxPolyDP(contours.get(i), Imgproc.arcLength(new MatOfPoint2f(contours.get(i).toArray()), true) * 0.02, true);
//square contours should have 4 vertices after approximation
//relatively large area (to filter out noisy contours)
//and be convex.
//Note: absolute value of an area is used because
//area may be positive or negative - in accordance with the
//contour orientation
double area = Imgproc.contourArea(approx);
if (area > 5000) {
if (approx.toArray().length == 4 &&
Math.abs(Imgproc.contourArea(approx)) > 1000 &&
Imgproc.isContourConvex(approx)) {
double maxCosine = 0;
Rect bitmap_rect = null;
for (int j = 2; j < 5; j++) {
//find the maximum cosine of the angle between joint edges
double cosine = Math.abs(angle(approx.toArray()[j % 4], approx.toArray()[j - 2], approx.toArray()[j - 1]));
maxCosine = Math.max(maxCosine, cosine);
bitmap_rect = new Rect(approx.toArray()[j % 4], approx.toArray()[j - 2]);
}
//if cosines of all angles are small
//(all angles are ~90 degree) then write quandrange
//vertices to resultant sequence
if (maxCosine < 0.3)
squares.add(approx);
}
}
}
}
}
}

Dans cette méthode, vous obtenez quatre points de document, puis vous pouvez couper cette image en utilisant la méthode ci-dessous:

      public Bitmap warpDisplayImage(Mat inputMat) {
List<Point> newClockVisePoints = new ArrayList<>();
int resultWidth = inputMat.width();
int resultHeight = inputMat.height();
Mat startM = Converters.vector_Point2f_to_Mat(orderRectCorners(Previes method four poit list(like : List<Point> points)));
Point ocvPOut4 = new Point(0, 0);
Point ocvPOut1 = new Point(0, resultHeight);
Point ocvPOut2 = new Point(resultWidth, resultHeight);
Point ocvPOut3 = new Point(resultWidth, 0);
ocvPOut3 = new Point(0, 0);
ocvPOut4 = new Point(0, resultHeight);
ocvPOut1 = new Point(resultWidth, resultHeight);
ocvPOut2 = new Point(resultWidth, 0);
}
Mat outputMat = new Mat(resultWidth, resultHeight, CvType.CV_8UC4);
List<Point> dest = new ArrayList<Point>();
dest.add(ocvPOut3);
dest.add(ocvPOut2);
dest.add(ocvPOut1);
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_CUBIC);
Bitmap descBitmap = Bitmap.createBitmap(outputMat.cols(), outputMat.rows(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(outputMat, descBitmap);
return descBitmap;
}