OpenCV——Brisk特征检测、匹配与对象查找

检测并绘制特征点：

#include <opencv2/opencv.hpp>
#include <opencv2/xfeatures2d.hpp>
#include <iostream>

using namespace cv;
using namespace cv::xfeatures2d;
using namespace std;

int main(int argc, char** argv) {
    Mat src = imread("test.jpg", IMREAD_GRAYSCALE);
    if (src.empty()) {
        printf("could not load image...
");
        return -1;
    }
    namedWindow("input image", CV_WINDOW_AUTOSIZE);
    imshow("input image", src);

    // BRISK特征点检测
    Ptr<BRISK> detector = BRISK::create();//创建一个BRISK类对象并初始化
    vector<KeyPoint> keypoints;
    detector->detect(src, keypoints, Mat());//找出关键点

    // 绘制关键点
    Mat keypoint_img;
    drawKeypoints(src, keypoints, keypoint_img, Scalar::all(-1), DrawMatchesFlags::DEFAULT);
    imshow("KeyPoints Image", keypoint_img);

    waitKey(0);
    return 0;
}

匹配：

#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>

using namespace cv;
using namespace std;

int main(int argc, char** argv) {
    Mat img1 = imread("fire_5.jpg", IMREAD_GRAYSCALE);
    Mat img2 = imread("数字.jpg", IMREAD_GRAYSCALE);
    if (img1.empty() || img2.empty()) {
        printf("could not load images...
");
        return -1;
    }
    imshow("box image", img1);
    imshow("scene image", img2);


    // extract akaze features
    Ptr<BRISK> detector = BRISK::create();
    vector<KeyPoint> keypoints_obj;
    vector<KeyPoint> keypoints_scene;
    Mat descriptor_obj, descriptor_scene;
    detector->detectAndCompute(img1, Mat(), keypoints_obj, descriptor_obj);
    detector->detectAndCompute(img2, Mat(), keypoints_scene, descriptor_scene);


    // matching
    FlannBasedMatcher matcher(new flann::LshIndexParams(20, 10, 2));
    //FlannBasedMatcher matcher;
    //FlannBasedMatcher matcher;
    vector<DMatch> matches;
    matcher.match(descriptor_obj, descriptor_scene, matches);

    // draw matches(key points)
    Mat akazeMatchesImg;
    /*
    drawMatches(img1, keypoints_obj, img2, keypoints_scene, matches, akazeMatchesImg);
    imshow("akaze match result", akazeMatchesImg);*/

    vector<DMatch> goodMatches;
    double minDist = 100000, maxDist = 0;
    for (int i = 0; i < descriptor_obj.rows; i++) {
        double dist = matches[i].distance;
        if (dist < minDist) {
            minDist = dist;
        }
        if (dist > maxDist) {
            maxDist = dist;
        }
    }
    printf("min distance : %f", minDist);

    for (int i = 0; i < descriptor_obj.rows; i++) {
        double dist = matches[i].distance;
        if (dist < max(1.5*minDist, 0.02)) {
            goodMatches.push_back(matches[i]);
        }
    }

    drawMatches(img1, keypoints_obj, img2, keypoints_scene, goodMatches, akazeMatchesImg, Scalar::all(-1),
        Scalar::all(-1), vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
    imshow("good match result", akazeMatchesImg);

    waitKey(0);
    return 0;
}