OPENCV feature Detector (Feature Detector), Description sub-extractor (descriptor Extractor) and description sub-match (descriptor Matcher)

1. Feature Detection Sub

-harris

Cv::cornerharris (image,strength,3,3,0.01);

-fast

CV::P tr<cv::fastfeaturedetector> fast = Cv::fastfeaturedetector::create ();

Or

Cv::fast (inputarray image, std::vector<keypoint> &keypoints, int threshold)

Or

Cv::fast (inputarray image, std::vector<keypoint> &keypoints, int threshold, bool nonmaxsuppression, int type)

-sift

CV::P tr<cv::xfeatures2d::sift> SIFT = Cv::xfeatures2d::sift::create ();

Or

<pre name= "code" class= "CPP" >CV::P tr<cv::xfeatures2d::siftfeaturedetector> sift = cv::xfeatures2d:: Siftfeaturedetector::create ();

-surf

CV::P tr<cv::xfeatures2d::surf> SURF = Cv::xfeatures2d::surf::create ();

Or

CV::P tr<cv::xfeatures2d::surffeaturedetector> surf = cv::xfeatures2d::surffeaturedetector::create ();

-orb

CV::P tr<cv::orb> ORB = Cv::orb::create ();

-mser

CV::P tr<cv::mser> mser = Cv::mser::create ();

-gftt

CV::P tr<cv::gfttdetector> GFTT = Cv::gfttdetector::create ();

or directly with goodfeaturestotrack function;

-agast

Cv::agast (inputarray image, std::vector<keypoint> &keypoints, int threshold)//or Cv::agast (Inputarray image, std::vector<keypoint> &keypoints, int threshold, bool nonmaxsuppression, int type)//or CV::P TR<CV:: agastfeaturedetector> agast = Cv::agastfeaturedetector::create ();

-brisk

CV::P tr<cv::brisk> brisk = Cv::brisk::create ();

-simpleblob

CV::P tr<cv::simpleblobdetector> blob = Cv::simpleblobdetector::create ();

-kaze

CV::P tr<cv::kaze> Kaze = Cv::kaze::create ();

-akaze

CV::P tr<cv::akaze> AKAZE = Cv::akaze::create ();

2. Description Sub-Extractor

-SIFT

<span style= "Font-weight:normal;" ><span style= "FONT-SIZE:12PX;" >CV::P tr<cv::xfeatures2d::sift> SIFT = Cv::xfeatures2d::sift::create ();//CV::P tr<cv::xfeatures2d:: Siftdescriptorextractor> sift = cv::xfeatures2d::siftdescriptorextractor::create ();</span></span>

-surf

<span style= "Font-weight:normal;" ><span style= "FONT-SIZE:12PX;" >CV::P tr<cv::xfeatures2d::surf> SURF = Cv::xfeatures2d::surf::create ();//CV::P tr<cv::xfeatures2d:: Surfdescriptorextractor> surf = cv::xfeatures2d::surfdescriptorextractor::create ();</span></span>

-brief

Brief is not used in OpenCV to extract descriptors, as it is used in the orb;

-brisk

<span style= "Font-weight:normal;" ><span style= "FONT-SIZE:12PX;" >CV::P tr<cv::brisk> brisk = cv::brisk::create ();</span></span>

-orb

<span style= "Font-size:12px;font-weight:normal;" >CV::P tr<cv::orb> ORB = cv::orb::create ();</span>

Orb is characterized by fast;

-kaze

<span style= "Font-size:12px;font-weight:normal;" >CV::P tr<cv::kaze> Kaze = cv::kaze::create ();</span>

Note: Kaze descriptors can only use Kaze or Akaze feature points;

-akaze

<span style= "Font-size:12px;font-weight:normal;" >CV::P tr<cv::akaze> AKAZE = cv::akaze::create ();</span>

Similarly, akaze descriptors can only use Kaze or Akaze feature points;

3. Description sub-matching device

   - Bruteforce-bfmatcher

CV::P tr<cv::bfmatcher> bf = cv::bfmatcher::create ("Bruteforce");

where the match type can also be a " BRUTEFORCE-L1 "," Bruteforce-l2 "," bruteforce-hamming ";

   - flannbased- Flannbasedmatcher

CV::P tr<cv::flannbasedmatcher> Flann = cv::flannbasedmatcher::create ("flannbased");

OPENCV feature Detector (Feature Detector), Description sub-extractor (descriptor Extractor) and description sub-match (descriptor Matcher)