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

这是第一张图的特征点检测结果:



这是第二张图的特征点检测:

翻译者¶

Shuai Zheng, <kylezheng04@gmail.com>, 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