文章目录
- 距的概念
- API函数
- 示例
距的概念
距的概念
API函数
moments(
InputArray array,//输入数据
bool binaryImage=false // 是否为二值图像
)contourArea(
InputArray contour,//输入轮廓数据
bool oriented// 默认false、返回绝对值)arcLength(
InputArray curve,//输入曲线数据
bool closed// 是否是封闭曲线)
示例
#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>using namespace std;
using namespace cv;Mat src, gray_src;
int threshold_value = 80;
int threshold_max = 255;
const char* output_win = "image moents demo";
RNG rng(12345);
void Demo_Moments(int, void*);
int main(int argc, char** argv) {src = imread("D:/vcprojects/images/circle.png");if (!src.data) {printf("could not load image...\n");return -1;}cvtColor(src, gray_src, CV_BGR2GRAY);GaussianBlur(gray_src, gray_src, Size(3, 3), 0, 0);char input_win[] = "input image";namedWindow(input_win, CV_WINDOW_AUTOSIZE);namedWindow(output_win, CV_WINDOW_AUTOSIZE);imshow(input_win, src);createTrackbar("Threshold Value : ", output_win, &threshold_value, threshold_max, Demo_Moments);Demo_Moments(0, 0);waitKey(0);return 0;
}void Demo_Moments(int, void*) {// 定义变量Mat canny_output; // Canny边缘检测的输出vector<vector<Point>> contours; // 图像中找到的轮廓vector<Vec4i> hierachy; // 轮廓的层级结构// 应用Canny边缘检测Canny(gray_src, canny_output, threshold_value, threshold_value * 2, 3, false);// 在二值图像中找到轮廓findContours(canny_output, contours, hierachy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));// 计算轮廓的矩和质心vector<Moments> contours_moments(contours.size()); // 轮廓的矩vector<Point2f> ccs(contours.size()); // 轮廓的质心for (size_t i = 0; i < contours.size(); i++) {// 计算轮廓的矩contours_moments[i] = moments(contours[i]); // 计算质心ccs[i] = Point(static_cast<float>(contours_moments[i].m10 / contours_moments[i].m00), static_cast<float>(contours_moments[i].m01 / contours_moments[i].m00)); }// 在原始图像上绘制轮廓和质心Mat drawImg; // 用于绘制轮廓和质心的图像src.copyTo(drawImg); // 复制原始图像以进行绘制for (size_t i = 0; i < contours.size(); i++) {// 跳过小轮廓if (contours[i].size() < 100) {continue;}// 为每个轮廓生成随机颜色Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));// 打印质心坐标和轮廓属性printf("center point x : %.2f y : %.2f\n", ccs[i].x, ccs[i].y);printf("contours %d area : %.2f arc length : %.2f\n", i, contourArea(contours[i]), arcLength(contours[i], true));// 在图像上绘制轮廓和质心drawContours(drawImg, contours, i, color, 2, 8, hierachy, 0, Point(0, 0));circle(drawImg, ccs[i], 2, color, 2, 8);}// 显示绘制了轮廓和质心的图像imshow(output_win, drawImg);return;
}