特征点描述
特征描述
目标
在本教程中,我们将涉及:
- 使用 DescriptorExtractor 接口来寻找关键点对应的特征向量. 特别地:
- 使用 SurfDescriptorExtractor 以及它的函数 compute 来完成特定的计算.
- 使用 BruteForceMatcher 来匹配特征向量。
- 使用函数 drawMatches 来绘制检测到的匹配点.
理论
代码
这个教程代码如下所示. 你还可以 从这里下载到源代码
#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 )
{ 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 )
{ 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 );
//-- Step 2: Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor;
Mat descriptors_1, descriptors_2;
extractor.compute( img_1, keypoints_1, descriptors_1 );
extractor.compute( img_2, keypoints_2, descriptors_2 );
//-- Step 3: Matching descriptor vectors with a brute force matcher
BruteForceMatcher< L2<float> > matcher;
std::vector< DMatch > matches;
matcher.match( descriptors_1, descriptors_2, matches );
//-- Draw matches
Mat img_matches;
drawMatches( img_1, keypoints_1, img_2, keypoints_2, matches, img_matches );
//-- Show detected matches
imshow("Matches", img_matches );
waitKey(0);
return 0;
}
/** @function readme */
void readme()
{ std::cout << " Usage: ./SURF_descriptor <img1> <img2>" << std::endl; }
解释
结果
-
这是使用BruteForce 匹配两张图的结果:
翻译者
Shuai Zheng, <kylezheng04@gmail.com>, http://www.cbsr.ia.ac.cn/users/szheng/