【OpenCV学习笔记 011】检测并匹配兴趣点

#include<iostream> #include<opencv2/core/core.hpp> #include<opencv2/highgui/highgui.hpp> #include<imgproc/imgproc.hpp> using namespace std; using namespace cv; class HarrisDetector{ private: //表示角点强度的32位浮点图像 Mat cornerStrength; //表示阈值化后角度的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; //阈值计算的最大强度 double maxStrength; //计算得到的阈值（内部） double thresholdValue; //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(3), aperture(3), k(0.01), maxStrength(0.0), thresholdValue(0.01), nonMaxSize(3){}; //创建非极大值抑制的核 void setLocalMaxWindowsize(int nonMaxSize){ this->nonMaxSize = nonMaxSize; } //计算Harris角点 void detect(const Mat&image){ //Harris计算 cornerHarris(image, cornerStrength, neighbourhood, //neighbourhood Size aperture, //滤波器的孔径大小 k); //Harris参数 //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); } //基于特定的阈值获取特征点 //由Harris值获取角点图 Mat getCornerMap(double qualityLevel){ Mat cornerMap; //对角点图像进行阈值化 thresholdValue = qualityLevel*maxStrength; threshold(cornerStrength, cornerTh, thresholdValue, 255, 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; } //由Harris值得到特征点 void getCorners(vector<Point>&points, double qualityLevel){ //得到角点图 Mat cornerMap = getCornerMap(qualityLevel); //得到角点 getCorners(points, cornerMap); } //由角点图获取特征点 void getCorners(vector<Point>&points, const Mat&cornerMap){ //遍历像素得到所有特征 for (int y = 0; y < cornerMap.rows; y++) { const uchar*rowPtr = cornerMap.ptr<uchar>(y); for (int x = 0; x < cornerMap.cols; x++) { //如果是特征点 if (rowPtr[x]) { points.push_back(Point(x, y)); } } } } void drawOnImage(Mat&image, const vector<Point>&points, Scalar color = Scalar(255, 255, 255), int radius = 3, int thickness = 2){ vector<Point>::const_iterator it = points.begin(); //对于所有角点 while (it != points.end()) { //绘制一个圆 circle(image, *it, radius, color, thickness); ++it; } } }; int main823(){ Mat image = cvLoadImage("church01.jpg"); Mat grayImage; cvtColor(image, grayImage, CV_BGR2GRAY); //创建Harris检测器的对象 HarrisDetector harris; // 改进的harris角点检测方法 std::vector<cv::Point> corners; cv::goodFeaturesToTrack(grayImage, corners, 500, //返回的最大特征点数目 0.01, // 质量等级，这里是0.01*max（min（e1，e2）），e1，e2是harris矩阵的特征值 10); // 两个角点之间的距离容忍度 harris.drawOnImage(grayImage, corners); //标记角点 namedWindow("harris"); imshow("harris", grayImage); waitKey(0); return 0; }