OpenCV图像特征提取之Shi-Tomasi角点检测算法详解

void GoodFeaturesToTrack
(            InputArray image, 
             OutputArray corners,
             int maxCorners, 
             double qualityLevel, 
             double minDistance,
             InputArray mask=noArray(), 
             int blockSize=3,
             bool useHarrisDetector=false, 
             double k=0.04 );

#include"stdafx.h"
#include <OpenCV2/opencv.hpp>
#include <iOStream>
 
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <iostream>
 
using namespace cv;
using namespace std;
 
#define WIN_NAME "Shi-Tomasi角点检测"
 
Mat srcImage, grayImage;
int maxCornerNumber = 33;
int maxTrackbarNumber = 500;
RNG rng(12345);
 
void on_GoodFeatureToTrack(int, void *)
{
    if (maxCornerNumber <= 1)
    {
        maxCornerNumber = 1;
    }
    //Shi-Tomasi参数准备
    vector<Point2f> corners;
    double qualityLevel = 0.01; //角点检测可以接受的最小特征值
    double minDistance = 10; //角点间的最小像素距离设置
    int blockSize = 3;  //计算导数自相关矩阵时指定的领域范围
    double k = 0.04;   //权重系数
 
    Mat copy = srcImage.clone(); //复制原图到一个临时变量中，作为感兴趣区域
                                 //Shi-Tomasi Test
    goodFeaturesToTrack(grayImage, corners, maxCornerNumber, qualityLevel, minDistance, Mat(), blockSize, false, k);
 
    //输出文字信息
    cout << ">此次检测到的角点数量为： " << corners.size() << endl;
 
    //绘制检测到的角点
    for (unsigned int i = 0; i < corners.size(); i++)
    {
        circle(copy, corners[i], 5, Scalar(rng.unifORM(0, 255), rng.uniform(0, 255), rng.uniform(0, 255)), -1, 8, 0);
    }
 
    imshow(WIN_NAME, copy);
}
 
int main(int arGC, char** argv)
{
    srcImage = imread("F:/photo/lj.jpg");
    cvtColor(srcImage, grayImage, COLOR_BGR2GRAY);
 
    namedWindow(WIN_NAME, WINDOW_AUTOSIZE);
 
    createTrackbar("最大角点数：", WIN_NAME, &maxCornerNumber, maxTrackbarNumber, on_GoodFeatureToTrack);
 
    //imshow(WIN_NAME, srcImage);
 
 
    on_GoodFeatureToTrack(0, 0);
 
 
    waiTKEy(0);
    return 0;
}