#include <iostream>
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui/highgui_c.h>
#include <opencv2\imgproc\types_c.h>
//sobel算子 /
//阶乘
int factorial(int n) {
int fac = 1;
//0的阶乘
if (n == 0)
return fac;
for (int i = 1; i <= n; ++i) {
fac *= i;
}
return fac;
}
//获得Sobel平滑算子
cv::Mat getSobelSmoooth(int wsize) {
int n = wsize - 1;
cv::Mat SobelSmooothoper = cv::Mat::zeros(cv::Size(wsize, 1), CV_32FC1);
for (int k = 0; k <= n; k++) {
float* pt = SobelSmooothoper.ptr<float>(0);
pt[k] = factorial(n) / (factorial(k) * factorial(n - k));
}
return SobelSmooothoper;
}
//获得Sobel差分算子
cv::Mat getSobeldiff(int wsize) {
cv::Mat Sobeldiffoper = cv::Mat::zeros(cv::Size(wsize, 1), CV_32FC1);
cv::Mat SobelSmoooth = getSobelSmoooth(wsize - 1);
for (int k = 0; k < wsize; k++) {
if (k == 0)
Sobeldiffoper.at<float>(0, k) = 1;
else if (k == wsize - 1)
Sobeldiffoper.at<float>(0, k) = -1;
else
Sobeldiffoper.at<float>(0, k) = SobelSmoooth.at<float>(0, k) - SobelSmoooth.at<float>(0, k - 1);
}
return Sobeldiffoper;
}
//卷积实现
void conv2D(cv::Mat& src, cv::Mat& dst, cv::Mat kernel, int ddepth, cv::Point anchor = cv::Point(-1, -1), int delta = 0, int borderType = cv::BORDER_DEFAULT) {
cv::Mat kernelFlip;
cv::flip(kernel, kernelFlip, -1);
cv::filter2D(src, dst, ddepth, kernelFlip, anchor, delta, borderType);
}
//可分离卷积———先垂直方向卷积，后水平方向卷积
void sepConv2D_Y_X(cv::Mat& src, cv::Mat& dst, cv::Mat kernel_Y, cv::Mat kernel_X, int ddepth, cv::Point anchor = cv::Point(-1, -1), int delta = 0, int borderType = cv::BORDER_DEFAULT) {
cv::Mat dst_kernel_Y;
conv2D(src, dst_kernel_Y, kernel_Y, ddepth, anchor, delta, borderType); //垂直方向卷积
conv2D(dst_kernel_Y, dst, kernel_X, ddepth, anchor, delta, borderType); //水平方向卷积
}
//可分离卷积———先水平方向卷积，后垂直方向卷积
void sepConv2D_X_Y(cv::Mat& src, cv::Mat& dst, cv::Mat kernel_X, cv::Mat kernel_Y, int ddepth, cv::Point anchor = cv::Point(-1, -1), int delta = 0, int borderType = cv::BORDER_DEFAULT) {
cv::Mat dst_kernel_X;
conv2D(src, dst_kernel_X, kernel_X, ddepth, anchor, delta, borderType); //水平方向卷积
conv2D(dst_kernel_X, dst, kernel_Y, ddepth, anchor, delta, borderType); //垂直方向卷积
}
//Sobel算子边缘检测
//dst_X 垂直方向
//dst_Y 水平方向
void Sobel(cv::Mat& src, cv::Mat& dst_X, cv::Mat& dst_Y, cv::Mat& dst, int wsize, int ddepth, cv::Point anchor = cv::Point(-1, -1), int delta = 0, int borderType = cv::BORDER_DEFAULT) {
cv::Mat SobelSmooothoper = getSobelSmoooth(wsize); //平滑系数
cv::Mat Sobeldiffoper = getSobeldiff(wsize); //差分系数
//可分离卷积———先垂直方向平滑，后水平方向差分——得到垂直边缘
sepConv2D_Y_X(src, dst_X, SobelSmooothoper.t(), Sobeldiffoper, ddepth);
//可分离卷积———先水平方向平滑，后垂直方向差分——得到水平边缘
sepConv2D_X_Y(src, dst_Y, SobelSmooothoper, Sobeldiffoper.t(), ddepth);
//边缘强度（近似）
dst = abs(dst_X) + abs(dst_Y);
cv::convertScaleAbs(dst, dst); //求绝对值并转为无符号8位图
}
//确定一个点的坐标是否在图像内
bool checkInRang(int r, int c, int rows, int cols) {
if (r >= 0 && r < rows && c >= 0 && c < cols)
return true;
else
return false;
}
//从确定边缘点出发，延长边缘
void trace(cv::Mat& edgeMag_noMaxsup, cv::Mat& edge, float TL, int r, int c, int rows, int cols) {
if (edge.at<uchar>(r, c) == 0) {
edge.at<uchar>(r, c) = 255;
for (int i = -1; i <= 1; ++i) {
for (int j = -1; j <= 1; ++j) {
float mag = edgeMag_noMaxsup.at<float>(r + i, c + j);
if (checkInRang(r + i, c + j, rows, cols) && mag >= TL)
trace(edgeMag_noMaxsup, edge, TL, r + i, c + j, rows, cols);
}
}
}
}
//Canny边缘检测
void Edge_Canny(cv::Mat& src, cv::Mat& edge, float TL, float TH, int wsize = 3, bool L2graydient = false) {
int rows = src.rows;
int cols = src.cols;
//高斯滤波
cv::GaussianBlur(src, src, cv::Size(5, 5), 0.8);
//sobel算子
cv::Mat dx, dy, sobel_dst;
Sobel(src, dx, dy, sobel_dst, wsize, CV_32FC1);
//计算梯度幅值
cv::Mat edgeMag;
if (L2graydient)
cv::magnitude(dx, dy, edgeMag); //开平方
else
edgeMag = abs(dx) + abs(dy); //绝对值之和近似
//计算梯度方向 以及 非极大值抑制
cv::Mat edgeMag_noMaxsup = cv::Mat::zeros(rows, cols, CV_32FC1);
for (int r = 1; r < rows - 1; ++r) {
for (int c = 1; c < cols - 1; ++c) {
float x = dx.at<float>(r, c);
float y = dy.at<float>(r, c);
float angle = std::atan2f(y, x) / CV_PI * 180; //当前位置梯度方向
float mag = edgeMag.at<float>(r, c); //当前位置梯度幅值
//非极大值抑制
//垂直边缘--梯度方向为水平方向-3*3邻域内左右方向比较
if (abs(angle) < 22.5 || abs(angle) > 157.5) {
float left = edgeMag.at<float>(r, c - 1);
float right = edgeMag.at<float>(r, c + 1);
if (mag >= left && mag >= right)
edgeMag_noMaxsup.at<float>(r, c) = mag;
}
//水平边缘--梯度方向为垂直方向-3*3邻域内上下方向比较
if ((angle >= 67.5 && angle <= 112.5) || (angle >= -112.5 && angle <= -67.5)) {
float top = edgeMag.at<float>(r - 1, c);
float down = edgeMag.at<float>(r + 1, c);
if (mag >= top && mag >= down)
edgeMag_noMaxsup.at<float>(r, c) = mag;
}
//+45°边缘--梯度方向为其正交方向-3*3邻域内右上左下方向比较
if ((angle > 112.5 && angle <= 157.5) || (angle > -67.5 && angle <= -22.5)) {
float right_top = edgeMag.at<float>(r - 1, c + 1);
float left_down = edgeMag.at<float>(r + 1, c - 1);
if (mag >= right_top && mag >= left_down)
edgeMag_noMaxsup.at<float>(r, c) = mag;
}
//+135°边缘--梯度方向为其正交方向-3*3邻域内右下左上方向比较
if ((angle >= 22.5 && angle < 67.5) || (angle >= -157.5 && angle < -112.5)) {
float left_top = edgeMag.at<float>(r - 1, c - 1);
float right_down = edgeMag.at<float>(r + 1, c + 1);
if (mag >= left_top && mag >= right_down)
edgeMag_noMaxsup.at<float>(r, c) = mag;
}
}
}
//双阈值处理及边缘连接
edge = cv::Mat::zeros(rows, cols, CV_8UC1);
for (int r = 1; r < rows - 1; ++r) {
for (int c = 1; c < cols - 1; ++c) {
float mag = edgeMag_noMaxsup.at<float>(r, c);
//大于高阈值，为确定边缘点
if (mag >= TH)
trace(edgeMag_noMaxsup, edge, TL, r, c, rows, cols);
else if (mag < TL)
edge.at<uchar>(r, c) = 0;
}
}
}
int main() {
cv::Mat src = cv::imread("C:\\Users\\yu\\Desktop\\21.jpg");
if (src.empty()) {
return -1;
}
if (src.channels() > 1)
{
cv::cvtColor(src, src, CV_RGB2GRAY);
}
cv::Mat edge;
//Canny
Edge_Canny(src, edge, 20, 60);
cv::namedWindow("My_canny", CV_WINDOW_NORMAL);
imshow("My_canny", edge);
cv::waitKey(0);
return 0;
}
