使用canny算法进行图像边缘检测

#include "cv.h" #include <math.h> #include <cmath> #include <iostream> #include <opencv2/opencv.hpp> using namespace cv; using namespace std; const float PI = 3.14159; void nonMaximumSuppression(Mat &mag, Mat &gau); void traceEdges(int x, int y, Mat &mag, int up, int low, Mat &result); void CannyED(Mat &img, Mat &result, int up, int low); void edgeDetection(Mat &mag, int up, int low, Mat &result); int main() { Mat img = imread("origin.png", 0); int upThrehold = 200; int lowThrehold = 100; Mat result; CannyED(img, result, upThrehold, lowThrehold); imshow("origin", img); imshow("result", result); imwrite("result.png", result); waitKey(); return 0; } void traceEdges(int x, int y, Mat &mag, int up, int low, Mat &result) { result.at<float>(y, x) = 255; for (int i = -1; i < 2; i++) { for (int j = -1; j < 2; j++) { if((i != 0) && (j != 0) && (x + i >= 0) && (y + j >= 0) && (x + i <= mag.cols-1) && (y + j <= mag.rows-1)){ if((mag.at<float>(y + j, x + i) > low) && (result.at<float>(y + j, x + i) != 255)) { traceEdges(x + i, y + j, mag, up, low, result); } } } } } void edgeDetection(Mat &mag, int up, int low, Mat &result) { int rows = mag.rows; int cols = mag.cols; result = Mat(mag.size(), CV_32F, 0.0); for (int x = 0; x < cols; x++) { for (int y = 0; y < rows; y++) { if (mag.at<float>(y, x) >= up){ traceEdges(x, y, mag, up, low, result); } } } } void nonMaximumSuppression(Mat &mag, Mat &gau) { Mat check = Mat(mag.rows, mag.cols, CV_8U); MatIterator_<float>itMag = mag.begin<float>(); MatIterator_<float>itGau= gau.begin<float>(); MatIterator_<float>itMagEnd = mag.end<float>(); MatIterator_<unsigned char>itCheck = check.begin<unsigned char>(); while(itMag != itMagEnd) { const Point pos = itCheck.pos(); float dir = atan(*itGau) * (180 / PI); while(dir < 0) dir += 180; *itGau = dir; if (dir > 22.5 && dir <= 67.5) { //如果当前像素点不是梯度方向最大点，将其设为0（背景色） if(pos.y > 0 && pos.x > 0 && *itMag <= mag.at<float>(pos.y - 1, pos.x - 1)) { mag.at<float>(pos.y, pos.x) = 0; } if(pos.y < mag.rows-1 && pos.x < mag.cols-1 && *itMag <= mag.at<float>(pos.y + 1, pos.x + 1)) { mag.at<float>(pos.y, pos.x) = 0; } } else if(dir > 67.5 && dir <= 112.5) { if(pos.y > 0 && *itMag <= mag.at<float>(pos.y-1, pos.x)) { mag.at<float>(pos.y, pos.x) = 0; } if(pos.y<mag.rows-1 && *itMag<=mag.at<float>(pos.y+1, pos.x)) { mag.at<float>(pos.y, pos.x) = 0; } } else if(dir > 112.5 && dir <= 157.5) { if(pos.y>0 && pos.x<mag.cols-1 && *itMag<=mag.at<float>(pos.y-1, pos.x+1)) { mag.at<float>(pos.y, pos.x) = 0;; } if(pos.y < mag.rows-1 && pos.x>0 && *itMag<=mag.at<float>(pos.y+1, pos.x-1)) { mag.at<float>(pos.y, pos.x) = 0; } } else { if(pos.x > 0 && *itMag <= mag.at<float>(pos.y, pos.x-1)) { mag.at<float>(pos.y, pos.x) = 0; } if(pos.x < mag.cols-1 && *itMag <= mag.at<float>(pos.y, pos.x+1)) { mag.at<float>(pos.y, pos.x) = 0; } } ++itGau; ++itCheck; ++itMag; } } void CannyED(Mat &img, Mat &result, int up, int low) { Mat img2 = img.clone(); //高斯模糊 GaussianBlur(img, img2, Size(3, 3), 1); //用Sobel算子计算梯度幅值和方向 Mat Gx = Mat(img.rows, img.cols, CV_32F); Mat Gy = Mat(img.rows, img.cols, CV_32F); Sobel(img2, Gx, CV_32F, 1, 0, 3); Sobel(img2, Gy, CV_32F, 0, 1, 3); Mat gau = Mat(img2.rows, img2.cols, CV_32F); //slopes = gy/gx divide(Gy, Gx, gau); //sum = gx^2 + gy^2 Mat sum = Mat(img2.rows, img2.cols, CV_64F); Mat x2 = Mat(img2.rows, img2.cols, CV_64F); Mat y2 = Mat(img2.rows, img2.cols, CV_64F); multiply(Gx, Gx, x2); multiply(Gy, Gy, y2); sum = x2 + y2; //sum = 根号sum sqrt(sum, sum); Mat magnitude = sum.clone(); //非极大值抑制 nonMaximumSuppression(magnitude, gau); //边缘检测 edgeDetection(magnitude, up, low, result); }