public void performMatch() {
// create feature detectors and feature extractors
FeatureDetector orbDetector = FeatureDetector.create(FeatureDetector.ORB);
DescriptorExtractor orbExtractor = DescriptorExtractor.create(DescriptorExtractor.ORB);
// set the keypoints
keyPointImg = new MatOfKeyPoint();
orbDetector.detect(imgGray, keyPointImg);
MatOfKeyPoint keyPointTempl = new MatOfKeyPoint();
orbDetector.detect(templGray, keyPointTempl);
// get the descriptions
descImg = new Mat(image.size(), image.type());
orbExtractor.compute(imgGray, keyPointImg, descImg);
Mat descTempl = new Mat(template.size(), template.type());
orbExtractor.compute(templGray, keyPointTempl, descTempl);
// perform matching
matches = new MatOfDMatch();
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
matcher.match(descImg, descTempl, matches);
Log.i("perform match result", matches.size().toString());
}
public void onCameraViewStarted(int width, int height) {
try {
detectThread = null;
if (detectThread == null) {
detectThread = new DetectThread();
thread = new Thread(detectThread);
thread.setPriority(Thread.MIN_PRIORITY);
thread.start();
}
// -- Step 1: Detect the keypoints using SURF Detector
featureDetector = FeatureDetector.create(FeatureDetector.FAST);
// -- Step 2: Calculate descriptors (feature vectors)
extractor = DescriptorExtractor.create(DescriptorExtractor.FREAK);
// -- Step 3: Matching descriptor vectors using FLANN matcher
matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_L1);
img_object = Utils.loadResource(this, R.drawable.cardobj, Highgui.CV_LOAD_IMAGE_GRAYSCALE);
img_scene = new Mat();
// img_scene = Utils.loadResource(this, R.drawable.cardscene,
// Highgui.CV_LOAD_IMAGE_GRAYSCALE);
matches = new MatOfDMatch();
listGoodMatches = new ArrayList<>();
keypoints_object = new MatOfKeyPoint();
keypoints_scene = new MatOfKeyPoint();
descriptors_object = new Mat();
descriptors_scene = new Mat();
obj = new MatOfPoint2f();
scene = new MatOfPoint2f();
H = new Mat();
obj_corners = new MatOfPoint2f();
scene_corners = new MatOfPoint2f();
min_dist = 9999999;
p0 = new Point(0, 0);
p1 = new Point(0, 0);
p2 = new Point(0, 0);
p3 = new Point(0, 0);
good_matches = new MatOfDMatch();
listPointScene = new ArrayList<>();
} catch (Exception ex) {
}
}
private Mat getTestDescriptors(Mat img) {
MatOfKeyPoint keypoints = new MatOfKeyPoint();
Mat descriptors = new Mat();
FeatureDetector detector = FeatureDetector.create(FeatureDetector.FAST);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.BRIEF);
detector.detect(img, keypoints);
extractor.compute(img, keypoints, descriptors);
return descriptors;
}
public Template performMatches(Map<String, Template> templates) {
// create feature detectors and feature extractors
FeatureDetector orbDetector = FeatureDetector.create(FeatureDetector.ORB);
DescriptorExtractor orbExtractor = DescriptorExtractor.create(DescriptorExtractor.ORB);
MatOfKeyPoint keyPointImgT;
Mat descImgT;
// set the keypoints
keyPointImgT = new MatOfKeyPoint();
orbDetector.detect(imgGray, keyPointImgT);
descImgT = new Mat(image.size(), image.type());
orbExtractor.compute(imgGray, keyPointImgT, descImgT);
Template best = null;
matches = null;
Map.Entry<String, Template> maxEntry = null;
// MatOfDMatch matches = new MatOfDMatch();
for (Map.Entry<String, Template> entry : templates.entrySet()) {
MatOfKeyPoint keyPointTempl = null;
Mat descTempl = null;
Mat tGray = null;
Template t = entry.getValue();
if (null == t.getTemplGray() || null == t.getDescTempl() || null == t.getKeyPointTempl()) {
// read image from stored data
Mat templ = readImgFromFile(t.getTemplName());
tGray = new Mat(templ.size(), templ.type());
Imgproc.cvtColor(templ, tGray, Imgproc.COLOR_BGRA2GRAY);
keyPointTempl = new MatOfKeyPoint();
orbDetector.detect(tGray, keyPointTempl);
descTempl = new Mat(templ.size(), templ.type());
orbExtractor.compute(tGray, keyPointTempl, descTempl);
t.setKeyPointTempl(keyPointTempl);
t.setDescTempl(descTempl);
} else {
descTempl = t.getDescTempl();
}
MatOfDMatch matchWithT = new MatOfDMatch();
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
// matcher.radiusMatch(descImgT, descTempl, matchWithT,200);//
matcher.match(descImgT, descTempl, matchWithT);
List<DMatch> matchList = matchWithT.toList();
// float min = Float.MAX_VALUE;
// float max = Float.MIN_VALUE;
// for(int i=0;i<matchList.size();i++){
// min = matchList.get(i).distance<min?matchList.get(i).distance:min;
// max = matchList.get(i).distance>max?matchList.get(i).distance:max;
// }
// Log.i("min distance","min distance is::"+min+"max
// distance::"+max+"size::"+matchList.size());
// Collections.sort(matchList, new Comparator<DMatch>() {
// @Override
// public int compare(DMatch o1, DMatch o2) {
// if (o1.distance < o2.distance)
// return -1;
// if (o1.distance > o2.distance)
// return 1;
// return 0;
// }
// });
float ratio = -1;
if (matchList.size() > 0) ratio = findMinTwoRatio(matchList);
if (ratio > 0.8 || ratio == -1) continue;
Log.i("match", "ratio::" + ratio);
// Todo:revisit logic
if (matches == null || (matchWithT.size().height > matches.size().height)) {
matches = matchWithT;
keyPointImg = keyPointImgT;
descImg = descImgT;
best = t;
}
}
// Log.i("perform match result", matches.size().toString());
return best;
}