OpenCV特征描述

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mob604756e58279 2016-03-18 15:20:00

文章标签 OpenCV 特征描述 #include 2d html 文章分类 虚拟化云计算

特征描述

目标

在本教程中，我们将涉及:

理论

代码

这个教程代码如下所示. 你还可以

#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; }