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, <[email protected]>, 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