Harris角点检测

代码示例一：

#include<opencv2/opencv.hpp>
using namespace cv;

int main(){
    Mat src = imread();
    imshow("原始图", src);

    //进行Harris角点检测找出角点
    Mat cornerStrength;
    cornerHarris(src, cornerStrength, , , 0.01);

    //对灰度图进行阈值操作，得到二值图并显示
    Mat harrisCorner;
    threshold(cornerStrength, harrisCorner, , THRESH_BINARY);
    imshow("二值效果图",harrisCorner);

    waitKey();
    ;
}

效果：

代码示例二：

#include<opencv2/opencv.hpp>
using namespace cv;

#define WINDOW_NAME1 "窗口1"
#define WINDOW_NAME2 "窗口2"

Mat src,srcClone,gray;
;
;

//函数声明
void onCornerHarris(int, void*);//回调函数

int main(){
    src = imread();
    imshow("原始图", src);
    srcClone = src.clone();
    cvtColor(srcClone, gray, COLOR_BGR2GRAY);

    //创建窗口和滚动条
    namedWindow(WINDOW_NAME1, WINDOW_AUTOSIZE);
    createTrackbar("阈值：", WINDOW_NAME1, &thresh, max_thresh, onCornerHarris);
    //调用一次回调函数进行初始化
    onCornerHarris(, );

    waitKey();
    ;
}

void onCornerHarris(int, void*){
    Mat dstImage;//目标图
    Mat normImage;//归一化后的图
    Mat scaledImage;//线性变换后的8位无符号整形图

    //初始化
    dstImage = Mat::zeros(src.size(), CV_32FC1);
    srcClone = src.clone();

    //进行角点检测
    cornerHarris(gray, dstImage, , , 0.04, BORDER_DEFAULT);
    //归一化与转换
    normalize(dstImage, normImage, , , NORM_MINMAX, CV_32FC1, Mat());
    convertScaleAbs(normImage, scaledImage);

    //绘制：将检测到的，符合阈值条件的角点绘制出来
    ; j < normImage.rows; j++){
        ; i < normImage.cols; i++){
            ){
                circle(srcClone, Point(i, j), , Scalar(, , ), , , );
                circle(scaledImage, Point(i, j), , Scalar(, , ), , , );
            }
        }
    }

    imshow(WINDOW_NAME1, srcClone);
    imshow(WINDOW_NAME2, scaledImage);
}

效果：

代码示例三：

#include<opencv2/opencv.hpp>
using namespace cv;
#include<vector>
using namespace std;
class HarrisDetector{
private:
    //表示角点强度的32位浮点图像
    Mat cornerStrength;
    //阈值化后的32位浮点图像
    Mat cornerTh;
    //局部极大值图像(内部)
    Mat localMax;
    //导数平滑的相邻像素的尺寸
    int neighbourhood;
    //梯度计算的孔径大小
    int aperture;
    //Harris参数
    double k;
    //harris计算的最大强度
    double maxStrength;
    //计算得到的阈值（内部）
    double threshold;
    //非极大值抑制的相邻像素的尺寸
    int nonMaxSize;
    //非极大值抑制的核
    Mat kernel;

public:
    HarrisDetector() :neighbourhood(), aperture(),
        k(0.01), maxStrength(0.0),
        threshold(){
        //创建非极大值抑制的核

    }

    void detect(const Mat& image){
        //harris计算
        cornerHarris(image, cornerStrength, neighbourhood, aperture, k);
        //内部阈值计算
        double minStrength;//未使用
        minMaxLoc(cornerStrength, &minStrength, &maxStrength);
        //局部极大值检测
        Mat dilated;//临时图像
        dilate(cornerStrength, dilated, Mat());
        compare(cornerStrength, dilated, localMax, CMP_EQ);
    }

    Mat getCornerMap(double qualityLevel){
        Mat cornerMap;
        //对角点图像进行阈值化
        this->threshold = qualityLevel*maxStrength;
        cv::threshold(cornerStrength, cornerTh, threshold, , THRESH_BINARY);
        //转换为8位图像
        cornerTh.convertTo(cornerMap,CV_8U);
        //非极大值抑制
        bitwise_and(cornerMap, localMax, cornerMap);
        return cornerMap;
    }

    void getCorners(vector<cv::Point>& points,double qualityLevel){
        //得到角点图
        cv::Mat cornerMap = getCornerMap(qualityLevel);
        getCorners(points, cornerMap);
    }

    void getCorners(vector<cv::Point>& points, const Mat& cornerMap){
        //遍历像素得到所有特征
        ; y < cornerMap.rows; y++){
            const uchar* rowPtr = cornerMap.ptr <uchar>(y);
            ; x < cornerMap.cols; x++){
                //如果是特征点
                if (rowPtr[x]){
                    points.push_back(cv::Point(x, y));
                }
            }
        }
    }

    //在特征点的位置绘制圆
    ,,), , ){
        vector<cv::Point>::const_iterator it = points.begin();
        while (it != points.end()){
            cv::circle(image, *it, radius, color, thickness);
            ++it;
        }
    }
};

int main(){
    Mat src = imread();
    //HarrisDetector类使用方式
    HarrisDetector harris;
    harris.detect(src);
    std::vector<cv::Point> pts;
    harris.getCorners(pts, 0.1);
    harris.drawOnImage(src, pts);
    imshow("result", src);
    waitKey();
}

效果：