 | 1 | initial version |
HI, I find the keypoint and the match between two images with BRISK ( I have to use it ) but now I need to use RANSAC to estimate the correspondence better than the only matcher function. Can you help me?
I think: I take the position of keypoint in the object and in the scene and calculate Homography with it, but i don't now how to continue.
Please help me.
| | 2 | No.2 Revision |
HI, I find the keypoint and the match between two images with BRISK ( I have to use it ) but now I need to use RANSAC to estimate the correspondence better than the only matcher function. Can you help me?
I think: I take the position of keypoint in the object and in the scene and calculate Homography with it, but i don't now how to continue.
Please help me.
This is my code:
Bitmap Matches(){
FeatureDetector detector;
MatOfKeyPoint keypoints1, keypoints2;
DescriptorExtractor descriptorExtractor;
Mat descriptors1, descriptors2;
DescriptorMatcher descriptorMatcher;
MatOfDMatch matches = new MatOfDMatch();
keypoints1 = new MatOfKeyPoint();
keypoints2 = new MatOfKeyPoint();
descriptors1 = new Mat();
descriptors2 = new Mat();
detector = FeatureDetector.create(FeatureDetector.BRISK);
descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.BRISK);
descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
detector.detect(immagine1,keypoints1);
detector.detect(immagine2, keypoints2);
descriptorExtractor.compute(immagine1, keypoints1, descriptors1);
descriptorExtractor.compute(immagine2, keypoints2, descriptors2);
descriptorMatcher.match(descriptors1, descriptors2, matches);
// Creo una lista di Keypoint della prima e della seconda immagine
List<KeyPoint> keypoints1_List = keypoints1.toList();
List<KeyPoint> keypoints2_List = keypoints2.toList();
// Creo la lista che conterrà i keypoint della seconda immagine che hanno matchato
List<KeyPoint> keypoint_scena_match = keypoints2.toList();
// matrice dei soli keypoint della scena che matchano
MatOfKeyPoint keypoint2_matched = new MatOfKeyPoint();
keypoint2_matched.fromList(keypoint_scena_match);
// Ottengo i punti dove si trovano i keypoint:
// Creo la lista dei punti di match tra oggetto e scena
LinkedList<Point> objList = new LinkedList<Point>();
LinkedList<Point> sceneList = new LinkedList<Point>();
// Creo la lista dei punti che hanno matchato
for (int i=0; i<descriptors1.rows();i++){
objList.addLast(keypoints1_List.get(matches.toList().get(i).queryIdx).pt);
sceneList.addLast(keypoints2_List.get(matches.toList().get(i).trainIdx).pt);
}
// Creo le matrici di punti che contengono i punti che matchano
MatOfPoint2f oggeto = new MatOfPoint2f();
MatOfPoint2f scena = new MatOfPoint2f();
oggeto.fromList(objList);
scena.fromList(sceneList);
// Trovo la trasformazione avvenuta tra una matrice e l'altra:
Mat H = Calib3d.findHomography(oggeto, scena, Calib3d.RANSAC, 10); // uso RANSAC
// Trovo la posizione dei keypoint tramite homografia
MatOfPoint2f oggetto_homografato = new MatOfPoint2f();
Imgproc.warpPerspective(oggeto, oggetto_homografato, H, new Size(immagine1.cols(), immagine1.rows()));
// prendo i keypoint giusti:
double dist_x = Math.abs(oggetto_homografato.toList().get(1).x-scena.toList().get(1).x);
double dist_y = Math.abs(oggetto_homografato.toList().get(1).y - scena.toList().get(1).y);
Toast.makeText(MainActivity.this,"Ho Trovato i match",Toast.LENGTH_SHORT).show();
/*
Mat src3 = new Mat();
Mat im1 = new Mat();
Mat im2 = new Mat();
Imgproc.cvtColor(immagine1, im1, Imgproc.COLOR_BGR2RGB);
Imgproc.cvtColor(immagine2, im2, Imgproc.COLOR_BGR2RGB);
Features2d.drawMatches(im1, keypoints1, im2, keypoints2, matches, src3);
Bitmap image1 = Bitmap.createBitmap(src3.cols(), src3.rows(), Bitmap.Config.ARGB_8888);
Imgproc.cvtColor(src3, src3, Imgproc.COLOR_RGB2BGR);
Utils.matToBitmap(src3, image1);
Toast.makeText(MainActivity.this,"Ho finito",Toast.LENGTH_SHORT).show();*/
return null; // for now is null but at the and it return the aside image of object and the scene
}
| | 3 | No.3 Revision |
HI, I find the keypoint and the match between two images with BRISK ( I have to use it ) but now I need to use RANSAC to estimate the correspondence better than the only matcher function. Can you help me?
I think: I take the position of keypoint in the object and in the scene and calculate Homography with it, but i don't now how to continue.
Please help me.
This is my code:
Bitmap Matches(){
FeatureDetector detector;
MatOfKeyPoint keypoints1, keypoints2;
DescriptorExtractor descriptorExtractor;
Mat descriptors1, descriptors2;
DescriptorMatcher descriptorMatcher;
MatOfDMatch matches = new MatOfDMatch();
keypoints1 = new MatOfKeyPoint();
keypoints2 = new MatOfKeyPoint();
descriptors1 = new Mat();
descriptors2 = new Mat();
detector = FeatureDetector.create(FeatureDetector.BRISK);
descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.BRISK);
descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
detector.detect(immagine1,keypoints1);
detector.detect(immagine2, keypoints2);
descriptorExtractor.compute(immagine1, keypoints1, descriptors1);
descriptorExtractor.compute(immagine2, keypoints2, descriptors2);
descriptorMatcher.match(descriptors1, descriptors2, descriptorMatcher.match(descriptors2, descriptors1, matches);
// Creo una lista di Keypoint della prima e della seconda immagine
//calculate max and min distances between keypoints
double max_dist=0;double min_dist=99;
List<DMatch> matchesList = matches.toList();
for(int i=0;i<descriptors2.rows();i++)
{
double dist = matchesList.get(i).distance;
if (dist<min_dist) min_dist = dist;
if (dist>max_dist) max_dist = dist;
}
//set up good matches, add matches if close enough
LinkedList<DMatch> good_matches = new LinkedList<DMatch>();
MatOfDMatch gm = new MatOfDMatch();
for (int i=0;i<descriptors1.rows();i++)
{
if(matchesList.get(i).distance<max_dist)
{
good_matches.addLast(matchesList.get(i));
}
}
gm.fromList(good_matches);
//put keypoints mats into lists
List<KeyPoint> keypoints1_List = keypoints1.toList();
List<KeyPoint> keypoints2_List = keypoints2.toList();
// Creo la lista che conterrà i keypoint della seconda immagine che hanno matchato
List<KeyPoint> keypoint_scena_match = keypoints2.toList();
// matrice dei soli keypoint della scena che matchano
MatOfKeyPoint keypoint2_matched = new MatOfKeyPoint();
keypoint2_matched.fromList(keypoint_scena_match);
// Ottengo i punti dove si trovano i keypoint:
// Creo la lista dei punti di match tra oggetto e scena
//put keypoints into point2f mats so calib3d can use them to find homography
LinkedList<Point> objList = new LinkedList<Point>();
LinkedList<Point> sceneList = new LinkedList<Point>();
// Creo la lista dei punti che hanno matchato
for (int i=0; i<descriptors1.rows();i++){
objList.addLast(keypoints1_List.get(matches.toList().get(i).queryIdx).pt);
sceneList.addLast(keypoints2_List.get(matches.toList().get(i).trainIdx).pt);
for(int i=0;i<good_matches.size();i++)
{
objList.addLast(keypoints1_List.get(good_matches.get(i).trainIdx).pt);
sceneList.addLast(keypoints2_List.get(good_matches.get(i).queryIdx).pt);
}
// Creo le matrici di punti che contengono i punti che matchano
MatOfPoint2f oggeto obj = new MatOfPoint2f();
MatOfPoint2f scena scene = new MatOfPoint2f();
oggeto.fromList(objList);
scena.fromList(sceneList);
// Trovo la trasformazione avvenuta tra una matrice e l'altra:
obj.fromList(objList);
scene.fromList(sceneList);
//output image
Mat outputImg = new Mat();
MatOfByte drawnMatches = new MatOfByte();
Features2d.drawMatches(immagine1, keypoints1, immagine2, keypoints2, gm, outputImg,
Scalar.all(-1), Scalar.all(-1), drawnMatches,Features2d.NOT_DRAW_SINGLE_POINTS);
//run homography on object and scene points
Mat H = Calib3d.findHomography(oggeto, scena, Calib3d.RANSAC, 10); Calib3d.findHomography(obj, scene,Calib3d.RANSAC, 5);
Mat tmp_corners = new Mat(4,1,CvType.CV_32FC2);
Mat scene_corners = new Mat(4,1,CvType.CV_32FC2);
//get corners from object
tmp_corners.put(0, 0, new double[] {0,0});
tmp_corners.put(1, 0, new double[] {immagine1.cols(),0});
tmp_corners.put(2, 0, new double[] {immagine1.cols(),immagine1.rows()});
tmp_corners.put(3, 0, new double[]{0, immagine1.rows()});
Core.perspectiveTransform(tmp_corners, scene_corners, H);
// uso RANSAC
find corner in the scene
Core.line(outputImg, new Point(scene_corners.get(0,0)),
new Point(scene_corners.get(1,0)), new Scalar(0, 255, 0),4);
Core.line(outputImg, new Point(scene_corners.get(1,0)),
new Point(scene_corners.get(2,0)), new Scalar(0, 255, 0),4);
Core.line(outputImg, new Point(scene_corners.get(2,0)),
new Point(scene_corners.get(3,0)), new Scalar(0, 255, 0),4);
Core.line(outputImg, new Point(scene_corners.get(3,0)),
new Point(scene_corners.get(0,0)), new Scalar(0, 255, 0),4);
// Trovo la posizione dei keypoint tramite homografia
MatOfPoint2f oggetto_homografato = new MatOfPoint2f();
Imgproc.warpPerspective(oggeto, oggetto_homografato, H, new Size(immagine1.cols(), immagine1.rows()));
// prendo i keypoint giusti:
double dist_x = Math.abs(oggetto_homografato.toList().get(1).x-scena.toList().get(1).x);
double dist_y = Math.abs(oggetto_homografato.toList().get(1).y - scena.toList().get(1).y);
Toast.makeText(MainActivity.this,"Ho Trovato i match",Toast.LENGTH_SHORT).show();
/*
Mat src3 = new Mat();
Mat im1 = new Mat();
Mat im2 = new Mat();
Imgproc.cvtColor(immagine1, im1, Imgproc.COLOR_BGR2RGB);
Imgproc.cvtColor(immagine2, im2, Imgproc.COLOR_BGR2RGB);
Features2d.drawMatches(im1, keypoints1, im2, keypoints2, matches, src3);
create the ouput image
Bitmap image1 = Bitmap.createBitmap(src3.cols(), src3.rows(), image_out = Bitmap.createBitmap(outputImg.cols(),outputImg.rows(), Bitmap.Config.ARGB_8888);
Imgproc.cvtColor(src3, src3, Imgproc.COLOR_RGB2BGR);
Utils.matToBitmap(src3, image1);
Toast.makeText(MainActivity.this,"Ho finito",Toast.LENGTH_SHORT).show();*/
//Imgproc.cvtColor(outputImg,outputImg,Imgproc.COLOR_GRAY2BGR);
Utils.matToBitmap(outputImg,image_out);
return null; // for now is null but at the and it return the aside image of object and the scene
image_out;
}
I think if I find the shape of the object and then apply to this the Hmography but my difficulty is to fine the shape, i try with findContours but it does not work i need the coordinate of the point with create the contours.
This is my new code and the result. Can you help me?
| | 4 | No.4 Revision |
HI, I find the keypoint and the match between two images with BRISK ( I have to use it ) but now I need to use RANSAC to estimate the correspondence better than the only matcher function. Can you help me?
I think: I take the position of keypoint in the object and in the scene and calculate Homography with it, but i don't now how to continue.
Please help me.
This is my code:
Bitmap Matches(){
FeatureDetector detector;
MatOfKeyPoint keypoints1, keypoints2;
DescriptorExtractor descriptorExtractor;
Mat descriptors1, descriptors2;
DescriptorMatcher descriptorMatcher;
MatOfDMatch matches = new MatOfDMatch();
keypoints1 = new MatOfKeyPoint();
keypoints2 = new MatOfKeyPoint();
descriptors1 = new Mat();
descriptors2 = new Mat();
detector = FeatureDetector.create(FeatureDetector.BRISK);
descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.BRISK);
descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
detector.detect(immagine1,keypoints1);
detector.detect(immagine2, keypoints2);
descriptorExtractor.compute(immagine1, keypoints1, descriptors1);
descriptorExtractor.compute(immagine2, keypoints2, descriptors2);
descriptorMatcher.match(descriptors2, descriptors1, matches);
//calculate max and min distances between keypoints
double max_dist=0;double min_dist=99;
List<DMatch> matchesList = matches.toList();
for(int i=0;i<descriptors2.rows();i++)
{
double dist = matchesList.get(i).distance;
if (dist<min_dist) min_dist = dist;
if (dist>max_dist) max_dist = dist;
}
//set up good matches, add matches if close enough
LinkedList<DMatch> good_matches = new LinkedList<DMatch>();
MatOfDMatch gm = new MatOfDMatch();
for (int i=0;i<descriptors1.rows();i++)
{
if(matchesList.get(i).distance<max_dist)
{
good_matches.addLast(matchesList.get(i));
}
}
gm.fromList(good_matches);
//put keypoints mats into lists
List<KeyPoint> keypoints1_List = keypoints1.toList();
List<KeyPoint> keypoints2_List = keypoints2.toList();
//put keypoints into point2f mats so calib3d can use them to find homography
LinkedList<Point> objList = new LinkedList<Point>();
LinkedList<Point> sceneList = new LinkedList<Point>();
for(int i=0;i<good_matches.size();i++)
{
objList.addLast(keypoints1_List.get(good_matches.get(i).trainIdx).pt);
sceneList.addLast(keypoints2_List.get(good_matches.get(i).queryIdx).pt);
}
MatOfPoint2f obj = new MatOfPoint2f();
MatOfPoint2f scene = new MatOfPoint2f();
obj.fromList(objList);
scene.fromList(sceneList);
//output image
Mat outputImg = new Mat();
MatOfByte drawnMatches = new MatOfByte();
Features2d.drawMatches(immagine1, keypoints1, immagine2, keypoints2, gm, outputImg,
Scalar.all(-1), Scalar.all(-1), drawnMatches,Features2d.NOT_DRAW_SINGLE_POINTS);
//run homography on object and scene points
Mat H = Calib3d.findHomography(obj, scene,Calib3d.RANSAC, 5);
10);
// trovo il contorno dell'oggetto
Mat tmp_corners = new Mat(4,1,CvType.CV_32FC2);
edges = new Mat();
Mat scene_corners = new Mat(4,1,CvType.CV_32FC2);
//get corners from object
tmp_corners.put(0, 0, new double[] {0,0});
tmp_corners.put(1, 0, new double[] {immagine1.cols(),0});
tmp_corners.put(2, 0, new double[] {immagine1.cols(),immagine1.rows()});
tmp_corners.put(3, 0, new double[]{0, immagine1.rows()});
Core.perspectiveTransform(tmp_corners, scene_corners, H);
hierarchy = new Mat();
// find corner in the scene
Core.line(outputImg, new Point(scene_corners.get(0,0)),
new Point(scene_corners.get(1,0)), new Scalar(0, 255, 0),4);
Core.line(outputImg, new Point(scene_corners.get(1,0)),
new Point(scene_corners.get(2,0)), new Scalar(0, 255, 0),4);
Core.line(outputImg, new Point(scene_corners.get(2,0)),
new Point(scene_corners.get(3,0)), new Scalar(0, 255, 0),4);
Core.line(outputImg, new Point(scene_corners.get(3,0)),
new Point(scene_corners.get(0,0)), new Scalar(0, 255, 0),4);
ogni contorno è una lista di punti
List<MatOfPoint> contourList = new ArrayList<MatOfPoint>(); // lista dei contorni
Imgproc.Canny(immagine1_grey, edges, 10, 100);
// Applico la trasformazione all'immagine
Mat bordi = new Mat(edges.cols(),edges.rows(),CvType.CV_32FC2);
Imgproc.warpPerspective(edges, bordi, H, new Size(edges.cols(), edges.rows()));
//Trovo i contorni
Imgproc.findContours(bordi,contourList,hierarchy,Imgproc.RETR_LIST,Imgproc.CHAIN_APPROX_SIMPLE);
// create the ouput image
Bitmap image_out = Bitmap.createBitmap(outputImg.cols(),outputImg.rows(), Bitmap.createBitmap(bordi.cols(),bordi.rows(), Bitmap.Config.ARGB_8888);
//Imgproc.cvtColor(outputImg,outputImg,Imgproc.COLOR_GRAY2BGR);
Utils.matToBitmap(outputImg,image_out);
Utils.matToBitmap(bordi,image_out);
return image_out;
}
I think if I find the shape Now i found the contours of the object and then apply to this the Hmography but my difficulty the tomography application is to fine the shape, i try not the image with findContours edges homograph but it does not work i need the coordinate of the point with create the contours.an image which don't have the contour.
This is my new code and the result. Can you help me?
| | 5 | No.5 Revision |
HI, I find the keypoint and the match between two images with BRISK ( I have to use it ) but now I need to use RANSAC to estimate the correspondence better than the only matcher function. Can you help me?
I think: I take the position of keypoint in the object and in the scene and calculate Homography with it, but i don't now how to continue.
Please help me.
This is my code:
Bitmap Matches(){
FeatureDetector detector;
MatOfKeyPoint keypoints1, keypoints2;
DescriptorExtractor descriptorExtractor;
Mat descriptors1, descriptors2;
DescriptorMatcher descriptorMatcher;
MatOfDMatch matches = new MatOfDMatch();
keypoints1 = new MatOfKeyPoint();
keypoints2 = new MatOfKeyPoint();
descriptors1 = new Mat();
descriptors2 = new Mat();
detector = FeatureDetector.create(FeatureDetector.BRISK);
descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.BRISK);
descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
detector.detect(immagine1,keypoints1);
detector.detect(immagine2, keypoints2);
descriptorExtractor.compute(immagine1, keypoints1, descriptors1);
descriptorExtractor.compute(immagine2, keypoints2, descriptors2);
descriptorMatcher.match(descriptors2, descriptors1, matches);
//calculate max and min distances between keypoints
double max_dist=0;double min_dist=99;
List<DMatch> matchesList = matches.toList();
for(int i=0;i<descriptors2.rows();i++)
{
double dist = matchesList.get(i).distance;
if (dist<min_dist) min_dist = dist;
if (dist>max_dist) max_dist = dist;
}
//set up good matches, add matches if close enough
LinkedList<DMatch> good_matches = new LinkedList<DMatch>();
MatOfDMatch gm = new MatOfDMatch();
for (int i=0;i<descriptors1.rows();i++)
{
if(matchesList.get(i).distance<max_dist)
{
good_matches.addLast(matchesList.get(i));
}
}
gm.fromList(good_matches);
//put keypoints mats into lists
List<KeyPoint> keypoints1_List = keypoints1.toList();
List<KeyPoint> keypoints2_List = keypoints2.toList();
//put keypoints into point2f mats so calib3d can use them to find homography
LinkedList<Point> objList = new LinkedList<Point>();
LinkedList<Point> sceneList = new LinkedList<Point>();
for(int i=0;i<good_matches.size();i++)
{
objList.addLast(keypoints1_List.get(good_matches.get(i).trainIdx).pt);
sceneList.addLast(keypoints2_List.get(good_matches.get(i).queryIdx).pt);
}
MatOfPoint2f obj = new MatOfPoint2f();
MatOfPoint2f scene = new MatOfPoint2f();
obj.fromList(objList);
scene.fromList(sceneList);
//output image
Mat outputImg = new Mat();
MatOfByte drawnMatches = new MatOfByte();
Features2d.drawMatches(immagine1, keypoints1, immagine2, keypoints2, gm, outputImg,
Scalar.all(-1), Scalar.all(-1), drawnMatches,Features2d.NOT_DRAW_SINGLE_POINTS);
//run homography on object and scene points
Mat H = Calib3d.findHomography(obj, scene,Calib3d.RANSAC, 10);
// trovo il contorno dell'oggetto
Mat edges = new Mat();
Mat hierarchy = new Mat();
// ogni contorno è una lista di punti
List<MatOfPoint> contourList = new ArrayList<MatOfPoint>(); // lista dei contorni
Imgproc.Canny(immagine1_grey, edges, 10, 100);
// Applico la trasformazione all'immagine
Mat bordi = new Mat(edges.cols(),edges.rows(),CvType.CV_32FC2);
Imgproc.warpPerspective(edges, bordi, H, new Size(edges.cols(), edges.rows()));
//Trovo i contorni
Imgproc.findContours(bordi,contourList,hierarchy,Imgproc.RETR_LIST,Imgproc.CHAIN_APPROX_SIMPLE);
Imgproc.findContours(edges,contourList,hierarchy,Imgproc.RETR_LIST,Imgproc.CHAIN_APPROX_SIMPLE);
MatOfPoint2f approxCurve = new MatOfPoint2f();
MatOfPoint points = null;
//For each contour found
for (int i=0; i<contourList.size(); i++)
{
//Convert contours(i) from MatOfPoint to MatOfPoint2f
MatOfPoint2f contour2f = new MatOfPoint2f( contourList.get(i).toArray() );
//Processing on mMOP2f1 which is in type MatOfPoint2f
double approxDistance = Imgproc.arcLength(contour2f, true)*0.02;
Imgproc.approxPolyDP(contour2f, approxCurve, approxDistance, true);
//Convert back to MatOfPoint
points = new MatOfPoint( approxCurve.toArray() );
// Get bounding rect of contour
Rect rect = Imgproc.boundingRect(points);
// draw enclosing rectangle (all same color, but you could use variable i to make them unique)
Core.rectangle(edges,new Point(rect.x,rect.y),
new Point(rect.x + rect.width,rect.y+rect.height),new Scalar(255,0,0),3);
}
MatOfPoint posizione = new MatOfPoint();
Imgproc.warpPerspective(points, posizione, H, new Size(points.cols(), points.rows())); // this is the problem
Rect rectangle = Imgproc.boundingRect(posizione);
Core.rectangle(immagine2_grey,new Point(rectangle.x,rectangle.y),
new Point(rectangle.x + rectangle.width,rectangle.y + rectangle.height),
new Scalar(255,0,0),1);
// create the ouput image
Bitmap image_out = Bitmap.createBitmap(bordi.cols(),bordi.rows(), Bitmap.Config.ARGB_8888);
//Imgproc.cvtColor(outputImg,outputImg,Imgproc.COLOR_GRAY2BGR);
Utils.matToBitmap(bordi,image_out);
Utils.matToBitmap(immagine2_grey,image_out);
return image_out;
}
Now My idea is:
1) Find the keypoint (done)
2) Find descriptor of keypoint (done)
3) Find homography transformation by RANSAC using calib3d ( the function in the code) and the position of keypoint which match (i think i found done it)
4) Find the contours of the object but the tomography application in the image one ( the object i want to find) (i think it work)
5) Find the position of the contours (i think it work )
6) Apply homography to the position of point 5 ( this is not the the problem )
7) Create a rectangle on the image 2( the scene) with the point obtained at the point 6 by homography
8) Create the final image with edges homograph but an image which don't have the contour.Features2d.drawmatches
This is my new code and the result. Can you help me?