Harris角点检测实现

 

 

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

using namespace cv;
using namespace std;
Mat src, gray_src;
int thresh = 130;
int max_count = 255;
const char* output_title = "HarrisCornerDetection Result";
void Harris_Demo(int, void*);
int main(int argc, char** argv) {

    src = imread("L:/6.jpg");
    if (src.empty()) {
        printf("could not load image...
");
        return -1;
    }
    namedWindow("input image", CV_WINDOW_AUTOSIZE);
    imshow("input image", src);

    namedWindow(output_title, CV_WINDOW_AUTOSIZE);
    cvtColor(src, gray_src, COLOR_BGR2GRAY);
    createTrackbar("Threshold:", output_title, &thresh, max_count, Harris_Demo);
    //&thresh为滑动窗口初始默认值130
    Harris_Demo(0, 0);

    waitKey(0);
    return 0;
}

void Harris_Demo(int, void*) {
    Mat dst, norm_dst, normScaleDst;
    dst = Mat::zeros(gray_src.size(), CV_32FC1);

    int blockSize = 2;  
    int ksize = 3;
    double k = 0.04;
    cornerHarris(gray_src, dst, blockSize, ksize, k, BORDER_DEFAULT);
    //参数：输入灰度图像，输出图像，blockSize参数矩阵的大小,ksize窗口大小，k角度响应参数0.04-0.06, 默认
    normalize(dst, norm_dst, 0, 255, NORM_MINMAX, CV_32FC1, Mat());
    //归一化函数：NORM_MINMAX为一般常用的方法，CV_32FC1 输出矩阵与输入矩阵类型相同
    convertScaleAbs(norm_dst, normScaleDst);
    //对矩阵取绝对值

    Mat resultImg = src.clone();
    // 克隆彩色图片src到resultImg

    for (int row = 0; row < resultImg.rows; row++) {
        uchar* currentRow = normScaleDst.ptr(row);       //行指针，指向一行的数据
        for (int col = 0; col < resultImg.cols; col++) {
            int value = (int)*currentRow;    //通过指针拿出数据值
            if (value > thresh) {
                circle(resultImg, Point(col, row), 2, Scalar(0, 0, 255), 2, 8, 0);
                //画圆
            }
            currentRow++;
        }
    }

    imshow(output_title, resultImg);
}

效果：