OpenCV 特征点检测

特征点检测

目标

在本教程中，我们将涉及:

• 使用 FeatureDetector 接口来发现感兴趣点。特别地:
  • 使用 SurfFeatureDetector 以及它的函数 detect 来实现检测过程
  • 使用函数 drawKeypoints 来绘制检测到的关键点

理论

代码

这个教程的代码如下所示。你还可以从 这个链接下载到源代码

#include <stdio.h>#include <iostream>#include "opencv2/core/core.hpp"#include "opencv2/features2d/features2d.hpp"#include "opencv2/highgui/highgui.hpp"using namespace cv;void readme();/** @function main */int main( int argc, char** argv ){  if( argc != 3 )  { readme(); return -1; }  Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );  Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );  if( !img_1.data || !img_2.data )  { std::cout<< " --(!) Error reading images " << std::endl; return -1; }  //-- Step 1: Detect the keypoints using SURF Detector  int minHessian = 400;  SurfFeatureDetector detector( minHessian );  std::vector<KeyPoint> keypoints_1, keypoints_2;  detector.detect( img_1, keypoints_1 );  detector.detect( img_2, keypoints_2 );  //-- Draw keypoints  Mat img_keypoints_1; Mat img_keypoints_2;  drawKeypoints( img_1, keypoints_1, img_keypoints_1, Scalar::all(-1), DrawMatchesFlags::DEFAULT );  drawKeypoints( img_2, keypoints_2, img_keypoints_2, Scalar::all(-1), DrawMatchesFlags::DEFAULT );  //-- Show detected (drawn) keypoints  imshow("Keypoints 1", img_keypoints_1 );  imshow("Keypoints 2", img_keypoints_2 );  waitKey(0);  return 0;  }  /** @function readme */  void readme()  { std::cout << " Usage: ./SURF_detector <img1> <img2>" << std::endl; }

解释

结果

1. 这是第一张图的特征点检测结果:

   

2. 这是第二张图的特征点检测:

   

翻译者¶

Shuai Zheng, <[e-mail]>, http://www.cbsr.ia.ac.cn/users/szheng/

from: http://www.opencv.org.cn/opencvdoc/2.3.2/html/doc/tutorials/features2d/feature_detection/feature_detection.html#feature-detection