java调用opencv的sift方法

简介: java调用opencv的sift方法

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代码找了好多,但是没有java版本的


网络异常,图片无法展示
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网络异常,图片无法展示
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public static void TestSift(Mat image1,Mat image2) {
Mat clone1=image1.clone();
Mat src1=image1.clone();
Mat clone2=image2.clone();
Mat src2=image2.clone();
Imgproc.GaussianBlur(clone1, clone1, new Size(3, 3), 0, 0);
Imgproc.cvtColor(clone1, clone1,Imgproc.COLOR_BGR2GRAY);
Imgproc.GaussianBlur(clone2, clone2, new Size(3, 3), 0, 0);
Imgproc.cvtColor(clone2, clone2,Imgproc.COLOR_BGR2GRAY);
MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
Mat des1=new Mat();
Mat des2=new Mat();
//  匹配的点数
SIFT sift=SIFT.create(200);
  //提取对象关键点
//  sift.detect(clone1,keypoints1);
//  sift.detect(clone2,keypoints2);
  //提取描述子
//  sift.compute(clone1,keypoints1, des1);
//  sift.compute(clone2,keypoints2, des2);
sift.detectAndCompute(clone1, new Mat(), keypoints1, des1);
sift.detectAndCompute(clone2, new Mat(), keypoints2, des2);
MatOfDMatch md=new  MatOfDMatch();
FlannBasedMatcher matcher=FlannBasedMatcher.create();
matcher.match(des1, des2, md);
double maxDist = 0;
double minDist = 50;
DMatch[] mats = md.toArray();
List<DMatch> bestMatches= new ArrayList<DMatch>();
for (int i = 0; i < mats.length; i++) {
  double dist = mats[i].distance;
  if (dist < minDist) {
    minDist = dist;
  }
  if (dist > maxDist) {
    maxDist = dist;
  }
}
System.out.println("max_dist : "+maxDist);
System.out.println("min_dist : "+minDist);
double threshold = 3 * minDist;
double threshold2 = 2 * minDist;
if (threshold2 >= maxDist){
    threshold = minDist * 1.1;
}
else if (threshold >= maxDist){
    threshold = threshold2 * 1.4;
}
if(0d==threshold) {
  threshold=0.3*maxDist;
}
System.out.println("Threshold : "+threshold);
for (int i = 0; i < mats.length; i++)
{
  //distance越小,代表DMatch的匹配率越高,
    Double dist = (double) mats[i].distance;
    System.out.println(String.format(i + " match distance best : %s", dist));
    if (dist <= threshold)
    {
        bestMatches.add(mats[i]);
        System.out.println(String.format(i + " best match added : %s", dist));
    }
}
md.fromList(bestMatches);
Mat result=new Mat();
Features2d.drawMatches(src1, keypoints1, src2, keypoints2, md, result);
HighGui.imshow("SIFT", result);
}
复制代码


knn写法


public static void TestSiftKnn(Mat image1,Mat image2) {
  //FastFeatureDetector detector = FastFeatureDetector.create(FastFeatureDetector.FAST_N);
  Mat clone1=image1.clone();
  Mat src1=image1.clone();
  Mat clone2=image2.clone();
  Mat src2=image2.clone();
  Imgproc.GaussianBlur(clone1, clone1, new Size(3, 3), 0, 0);
  Imgproc.cvtColor(clone1, clone1,Imgproc.COLOR_BGR2GRAY);
  Imgproc.GaussianBlur(clone2, clone2, new Size(3, 3), 0, 0);
  Imgproc.cvtColor(clone2, clone2,Imgproc.COLOR_BGR2GRAY);
  MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
  MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
  Mat des1=new Mat();
  Mat des2=new Mat();
  SIFT sift=SIFT.create(200);
  //提取对象关键点
//  sift.detect(clone1,keypoints1);
//  sift.detect(clone2,keypoints2);
  //提取描述子
//  sift.compute(clone1,keypoints1, des1);
//  sift.compute(clone2,keypoints2, des2);
  sift.detectAndCompute(clone1, new Mat(), keypoints1, des1);
  sift.detectAndCompute(clone2, new Mat(), keypoints2, des2);
  MatOfDMatch md=new  MatOfDMatch();
  FlannBasedMatcher matcher=FlannBasedMatcher.create();
  //matcher.match(des1, des2, md);
  List<Mat> matList=new ArrayList<Mat>();
  List<MatOfDMatch> mdList=new ArrayList<MatOfDMatch>();
  matList.add(des1);
    matcher.add(matList);
    matcher.train();
    matcher.knnMatch(des2, mdList, 2);
    List<DMatch> dMatchList = new ArrayList<DMatch>();
    Iterator<MatOfDMatch> ite=mdList.iterator();
    while(ite.hasNext()) {
      MatOfDMatch next=ite.next();
      if (next.toArray()[0].distance < 0.2 * next.toArray()[1].distance) {
        System.out.println(next.toArray()[0].distance+"->"+next.toArray()[1].distance);
        dMatchList.add(next.toArray()[0]);
      }else {
        ite.remove();
      }
    }
   md.fromList(dMatchList);
  Mat result=new Mat();
//  Features2d.drawMatches(src1, keypoints1, src2, keypoints2, md, result);
  Features2d.drawMatchesKnn(src1, keypoints1, src2, keypoints2, mdList, result);
  HighGui.imshow("SIFT", result);
}


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