错误的匹配与ORB在安卓 [英] Error matching with ORB in Android
本文介绍了错误的匹配与ORB在安卓的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我的code的工作很好，但是当它提取关键点，它匹配不佳的两个图像。
在这里，你可以找到我的code，但我不知道该如何绘制 JAVA Android的良好匹配
描述符=新垫（）;
关键点=新MatOfKeyPoint（）;
探测器= FeatureDetector.create（FeatureDetector.ORB）;
detector.detect（IMG1，关键点）;
描述= DescriptorExtractor.create（DescriptorExtractor.ORB）;
descriptor.compute（IMG1，关键点，描述符）;
匹配= DescriptorMatcher.create（DescriptorMatcher.BRUTEFORCE_HAMMING）;
ColorDetection.cvt_YUVtoRGBtoHSV（mYuv，mGraySubmat）;
MatOfKeyPoint mKeyPoints =新MatOfKeyPoint（）;
MatOfDMatch匹配=新MatOfDMatch（）;
detector.detect（mGraySubmat，mKeyPoints）;
descriptor.compute（mGraySubmat，mKeyPoints，mIntermediateMat）;
matcher.match（mIntermediateMat，描述符，匹配）;
mIntermediateMat2.create（resultSize，CvType.CV_8UC1）;
Features2d.drawMatches（IMG1，关键点，mGraySubmat，mKeyPoints，比赛中，
mIntermediateMat2，绿色，红色，MATCH_MASK，Features2d.NOT_DRAW_SINGLE_POINTS）;
Imgproc.resize（mIntermediateMat2，mIntermediateMat2，mRgba.size（））;
Imgproc.cvtColor（mIntermediateMat2，mRgba，Imgproc.COLOR_RGBA2BGRA，4）;
Utils.matToBitmap（mRgba，BMP）;
DMatch DM [] = matches.toArray（）;
名单＆LT;点＆GT; LP1 =新的ArrayList＆LT;点＆GT;（dm.length）;
名单＆LT;点＆GT; LP2 =新的ArrayList＆LT;点＆GT;（dm.length）;
关键点TKP [] = keypoints.toArray（）;
关键点QKP [] = mKeyPoints.toArray（）;
的for（int i = 0; I＆LT; dm.length;我++）{
DMatch DMA = DM [I]
lp1.add（TKP [dma.trainIdx] .PT）;
lp2.add（QKP [dma.queryIdx] .PT）;
}
MatOfPoint2f点preV =新MatOfPoint2f（lp1.toArray（新点[0]））;
MatOfPoint2f pointsAct =新MatOfPoint2f（lp2.toArray（新点[0]））;
Log.i（点preV，点prev.size（）的toString（））;
Log.i（pointsAct，pointsAct.size（）的toString（））;
fundamental_matrix.create（resultSize，CvType.CV_8UC1）;
fundamental_matrix = Calib3d.findFundamentalMat（
pointsAct，点preV，Calib3d.FM_RANSAC，3，0.99）;
任何建议？
编辑：
我不能转换火柴名单！因为 Feature2d.drawMatches（）
需要一个 MatOfDmatch ，而不是名单，其中，Dmatch＆GT;
MatOfDMatch匹配，matches12，matches21;
matcher.match（descriptors1，descriptors2，matches12）;
matcher.match（descriptors2，descriptors1，matches21）;
迭代matches12
DMatch向前= matches12 [I]
DMatch落后= matches21 [forward.trainIdx]
如果（backward.trainIdx == forward.queryIdx）
//着增加比赛
Features2d.drawMatches（IMG1，关键点，mGraySubmat，mKeyPoints，火柴，mIntermediateMat2）;
解决方案
您code应该是这样的：
FeatureDetector探测器= FeatureDetector.create（FeatureDetector.ORB）;
DescriptorExtractor描述符= DescriptorExtractor.create（DescriptorExtractor.ORB）;;
DescriptorMatcher匹配= DescriptorMatcher.create（DescriptorMatcher.BRUTEFORCE_HAMMING）;
//第一个图像
垫IMG1 = Highgui.imread（＆LT;此搜索路径＆gt;中）;
垫descriptors1 =新垫（）;
MatOfKeyPoint keypoints1 =新MatOfKeyPoint（）;
detector.detect（IMG1，keypoints1）;
descriptor.compute（IMG1，keypoints1，descriptors1）;
//第二图像
垫IMG2 = Highgui.imread（＆LT; IMAGE2路径＆gt;中）;
垫descriptors2 =新垫（）;
MatOfKeyPoint keypoints2 =新MatOfKeyPoint（）;
detector.detect（IMG2，keypoints2）;
descriptor.compute（IMG2，keypoints2，descriptors2）;
//匹配应该包括2个不同形象的描述
MatOfDMatch匹配=新MatOfDMatch（）;
matcher.match（descriptors1，descriptors2，匹配）;
//功能和连接的颜色
标红=新的标量（255,0,0）;
标绿色=新的标量（0,255,0）;
//输出图像
垫outputImg =新垫（）;
MatOfByte drawnMatches =新MatOfByte（）;
//这将吸引所有的比赛，工作正常
Features2d.drawMatches（IMG1，keypoints1，IMG2，keypoints2，火柴，
outputImg，绿色，红色，drawnMatches，Features2d.NOT_DRAW_SINGLE_POINTS）;
另外，如果你想只显示功能，您可以添加这个code：
垫featuredImg =新垫（）;
标量kpColor =新的标量（255,159,10）; //这将是关键点颜色
// featuredImg将第一图像的输出
Features2d.drawKeypoints（IMG1，keypoints1，featuredImg，kpColor，0）;
// featuredImg将第一图像的输出
Features2d.drawKeypoints（IMG1，keypoints1，featuredImg，kpColor，0）;
然后就可以显示匹配点是这样的：
位图imageMatched = Bitmap.createBitmap（outputImg.cols（），outputImg.rows（），Bitmap.Config.RGB_565）; //需要保存的位图
Utils.matToBitmap（outputImg，imageMatched）;
ImageView.setImageBitmap（imageMatched）;
最后，你可以实现良好的匹配。我希望这个线程会有所帮助。
My code is working good but when it extracts keypoints, it matches poorly the two images.
Here you can find my code, but I don't know how to draw good matched in JAVA Android
descriptors = new Mat();
keypoints = new MatOfKeyPoint();
detector = FeatureDetector.create(FeatureDetector.ORB);
detector.detect(img1, keypoints);
descriptor = DescriptorExtractor.create(DescriptorExtractor.ORB);
descriptor.compute(img1, keypoints, descriptors);
matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
ColorDetection.cvt_YUVtoRGBtoHSV(mYuv,mGraySubmat);
MatOfKeyPoint mKeyPoints = new MatOfKeyPoint();
MatOfDMatch matches = new MatOfDMatch();
detector.detect(mGraySubmat, mKeyPoints);
descriptor.compute(mGraySubmat, mKeyPoints, mIntermediateMat);
matcher.match(mIntermediateMat,descriptors,matches);
mIntermediateMat2.create(resultSize, CvType.CV_8UC1);
Features2d.drawMatches(img1, keypoints, mGraySubmat, mKeyPoints, matches,
mIntermediateMat2,GREEN, RED, MATCH_MASK, Features2d.NOT_DRAW_SINGLE_POINTS);
Imgproc.resize(mIntermediateMat2, mIntermediateMat2, mRgba.size());
Imgproc.cvtColor(mIntermediateMat2, mRgba, Imgproc.COLOR_RGBA2BGRA, 4);
Utils.matToBitmap(mRgba, bmp);
DMatch dm[] = matches.toArray();
List<Point> lp1 = new ArrayList<Point>(dm.length);
List<Point> lp2 = new ArrayList<Point>(dm.length);
KeyPoint tkp[] = keypoints.toArray();
KeyPoint qkp[] = mKeyPoints.toArray();
for (int i = 0; i < dm.length; i++) {
DMatch dma = dm[i];
lp1.add(tkp[dma.trainIdx].pt);
lp2.add(qkp[dma.queryIdx].pt);
}
MatOfPoint2f pointsPrev = new MatOfPoint2f(lp1.toArray(new Point[0]));
MatOfPoint2f pointsAct = new MatOfPoint2f(lp2.toArray(new Point[0]));
Log.i("pointsPrev", pointsPrev.size().toString());
Log.i("pointsAct", pointsAct.size().toString());
fundamental_matrix.create(resultSize, CvType.CV_8UC1);
fundamental_matrix = Calib3d.findFundamentalMat(
pointsAct, pointsPrev, Calib3d.FM_RANSAC, 3, 0.99);
any suggestion?
EDIT :
i can't convert matches to list ! because Feature2d.drawMatches()
need a MatOfDmatch and not a List<Dmatch>
MatOfDMatch matches, matches12, matches21;
matcher.match( descriptors1, descriptors2, matches12 );
matcher.match( descriptors2, descriptors1, matches21 );
iterate matches12
DMatch forward = matches12[i];
DMatch backward = matches21[forward.trainIdx];
if( backward.trainIdx == forward.queryIdx )
//add forward to matches
Features2d.drawMatches(img1, keypoints, mGraySubmat, mKeyPoints, matches,mIntermediateMat2);
解决方案
Your code should be like this:
FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
DescriptorExtractor descriptor = DescriptorExtractor.create(DescriptorExtractor.ORB);;
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
//first image
Mat img1 = Highgui.imread("<image1 path>");
Mat descriptors1 = new Mat();
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
detector.detect(img1, keypoints1);
descriptor.compute(img1, keypoints1, descriptors1);
//second image
Mat img2 = Highgui.imread("<image2 path>");
Mat descriptors2 = new Mat();
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
detector.detect(img2, keypoints2);
descriptor.compute(img2, keypoints2, descriptors2);
//matcher should include 2 different image's descriptors
MatOfDMatch matches = new MatOfDMatch();
matcher.match(descriptors1,descriptors2,matches);
//feature and connection colors
Scalar RED = new Scalar(255,0,0);
Scalar GREEN = new Scalar(0,255,0);
//output image
Mat outputImg = new Mat();
MatOfByte drawnMatches = new MatOfByte();
//this will draw all matches, works fine
Features2d.drawMatches(img1, keypoints1, img2, keypoints2, matches,
outputImg, GREEN, RED, drawnMatches, Features2d.NOT_DRAW_SINGLE_POINTS);
Also if you want to display just features, you can add this code:
Mat featuredImg = new Mat();
Scalar kpColor = new Scalar(255,159,10);//this will be color of keypoints
//featuredImg will be the output of first image
Features2d.drawKeypoints(img1, keypoints1, featuredImg , kpColor, 0);
//featuredImg will be the output of first image
Features2d.drawKeypoints(img1, keypoints1, featuredImg , kpColor, 0);
Then you can show matched points like this:
Bitmap imageMatched = Bitmap.createBitmap(outputImg.cols(), outputImg.rows(), Bitmap.Config.RGB_565);//need to save bitmap
Utils.matToBitmap(outputImg, imageMatched);
ImageView.setImageBitmap(imageMatched);
Eventually you can implement good matches. I hope this thread will be helpful.
这篇关于错误的匹配与ORB在安卓的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
查看全文
