目前我正在使用OpenCV来比较两张图片,看看它们在Android中是否相似。我正在使用ORB特征检测器和描述符提取器。这是我到目前为止所拥有的。我找到第一张图像中的所有特征关键点,然后找到第二张图像中的所有特征关键点。然后我找到这些关键点的描述符,然后在两个图像之间进行匹配。
private void matchImages() {
Mat refMat = new Mat();
Mat srcMat = new Mat();
Bitmap refBitmap = ((BitmapDrawable) mRefImg.getDrawable()).getBitmap();
Bitmap srcBitmap = ((BitmapDrawable) mSrcImg.getDrawable()).getBitmap();
Utils.bitmapToMat(refBitmap, refMat);
Utils.bitmapToMat(srcBitmap, srcMat);
MatOfDMatch matches = new MatOfDMatch();
MatOfDMatch goodMatches = new MatOfDMatch();
LinkedList<DMatch> listOfGoodMatches = new LinkedList<>();
LinkedList<Point> refObjectList = new LinkedList<>();
LinkedList<Point> srcObjectList = new LinkedList<>();
MatOfKeyPoint refKeypoints = new MatOfKeyPoint();
MatOfKeyPoint srcKeyPoints = new MatOfKeyPoint();
Mat refDescriptors = new Mat();
Mat srcDescriptors = new Mat();
MatOfPoint2f reference = new MatOfPoint2f();
MatOfPoint2f source = new MatOfPoint2f();
FeatureDetector orbFeatureDetector = FeatureDetector.create(FeatureDetector.ORB);
orbFeatureDetector.detect(refMat, refKeypoints);
orbFeatureDetector.detect(srcMat, srcKeyPoints);
DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.ORB);
descriptorExtractor.compute(refMat, refKeypoints, refDescriptors);
descriptorExtractor.compute(srcMat, srcKeyPoints, srcDescriptors);
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
matcher.match(refDescriptors, srcDescriptors, matches);
double max_dist = 0;
double min_dist = 100;
List<DMatch> matchesList = matches.toList();
for (int i = 0; i < refDescriptors.rows(); i++) {
Double distance = (double) matchesList.get(i).distance;
if (distance < min_dist) min_dist = distance;
if (distance > max_dist) max_dist = distance;
}
for (int i = 0; i < refDescriptors.rows(); i++) {
if (matchesList.get(i).distance < 3 * min_dist) {
listOfGoodMatches.add(matchesList.get(i));
}
}
goodMatches.fromList(listOfGoodMatches);
List<KeyPoint> refObjectListKeypoints = refKeypoints.toList();
List<KeyPoint> srcObjectListKeypoints = srcKeyPoints.toList();
for (int i = 0; i < listOfGoodMatches.size(); i++) {
refObjectList.addLast(refObjectListKeypoints.get(listOfGoodMatches.get(i).queryIdx).pt);
srcObjectList.addLast(srcObjectListKeypoints.get(listOfGoodMatches.get(i).trainIdx).pt);
}
reference.fromList(refObjectList);
source.fromList(srcObjectList);
String result;
if(listOfGoodMatches.size() > MIN_MATCH_THRESHOLD && listOfGoodMatches.size() < MAX_MATCH_THRESHOLD) {
result = "They MATCH!";
} else {
result = "They DON'T match!";
}
AlertDialog alert = new AlertDialog.Builder(this)
.setMessage(result)
.setPositiveButton("OK", new DialogInterface.OnClickListener() {
@Override
public void onClick(DialogInterface dialog, int which) {
// close
}
}).create();
alert.show();
Mat outputImage = new Mat();
Bitmap comboBmp = combineImages(refBitmap, srcBitmap);
Utils.bitmapToMat(comboBmp, outputImage);
Features2d.drawMatches(refMat, refKeypoints, srcMat, srcKeyPoints, goodMatches, outputImage);
Bitmap bitmap = Bitmap.createBitmap(outputImage.cols(), outputImage.rows(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(outputImage, bitmap);
mRefImg.setImageBitmap(comboBmp);
mRefImg.invalidate();
mSrcImg.setImageBitmap(bitmap);
mSrcImg.invalidate();
}
这只是一个简单的沙盒&#39;我创建的应用程序只是为了测试和使用这个库。如果我比较两个图像,上面代码的结果会产生以下结果:
如您所见,比赛的背景是黑色的。如何在左侧图像上绘制这些匹配?我希望我的结果看起来像一个例子:https://stackoverflow.com/a/14909358/3779845
答案 0 :(得分:8)
我不确定这对你是否仍然有任何帮助,但我如何修复黑色背景问题而不是使用我使用过的RGBA图像
Imgproc.cvtColor(gabarito, gabaritoRgb, Imgproc.COLOR_RGBA2RGB, 1);
Imgproc.cvtColor(prova, provaRgb, Imgproc.COLOR_RGBA2RGB, 1);
将我的图像转换为RGB,然后我在drawMatched函数中使用了新图像!
Features2d.drawMatches(gabaritoRgb, keypointsGabarito, provaRgb, keypointsProva, matches,
imagemDeSaida);