android - 如何减少 OpenCV 模式识别中的匹配？

Question

您好，我正在开发识别模式的 Android 应用程序，如您所见，它可以正常工作，但我不得不面对过度匹配的问题。我读到这是因为我的匹配器太敏感了。为了匹配，我使用这种匹配器:

DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);

...

matcher.match(descriptor1, descriptorLogo, matches);

我也尝试实现 knnmatch() 但这是因为我无法使用函数 Features2d.drawMatches()

感谢您的回答，希望能解决我的问题

Answer 1

有几种技术可以去除异常值或优化匹配:

• 交叉检查

• 比率测试

• RANSAC+平面形状的单应性

我通常应用最后两个。

比率测试:

BFMatchermatcher(CV_L2);
vector<vector<DMatch>>nearest_neighbors;
matcher.radiusMatch(
right_points_to_find_flat,
right_features_flat,
nearest_neighbors,
2.0f);

// Check that the found neighbors are unique (throw away neighbors
//  that are too close together, as they may be confusing)
std::set<int>found_in_right_points; // for duplicate prevention
for(inti=0;i<nearest_neighbors.size();i++) {
DMatch _m;
if(nearest_neighbors[i].size()==1) {
    _m = nearest_neighbors[i][0]; // only one neighbor
} else if(nearest_neighbors[i].size()>1) {
        // 2 neighbors – check how close they are
        double ratio = nearest_neighbors[i][0].distance / nearest_neighbors[i][1].distance;
if(ratio < 0.7) { // not too close
    // take the closest (first) one
    _m = nearest_neighbors[i][0];
} else { // too close – we cannot tell which is better
        continue; // did not pass ratio test – throw away
}
} else {
        continue; // no neighbors... :(
}

RANSAC+单应性:

std::vector<Point2f> object;
  std::vector<Point2f> scene;

  for( int i = 0; i < good_matches.size(); i++ )
  {
    //-- Get the keypoints from the good matches
    object.push_back( keypoints_object[ good_matches[i].queryIdx ].pt );
    scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );
  }
  Mat H = findHomography( object, scene, CV_RANSAC, status );

  //draw only the matches considered inliers by RANSAC => status=1
  for(i=0;i=object.size();i++){
  if(status[i])
  {
  }
  }