OpenCV的图像矩(64)

返回:OpenCV系列文章目录（持续更新中......）

上一篇：OpenCV如何为等值线创建边界旋转框和椭圆(63)

下一篇 :OpenCV系列文章目录（持续更新中......）

Image Moments（图像矩）是 OpenCV 库中的一个功能，它可以用于计算图像的重心、面积、方向等特征，是图像分析和处理中常用的重要工具之一。在计算机视觉领域中，许多图像处理算法都需要依赖于图像矩作为输入，例如对象识别、运动跟踪、形状分析等。图像矩的计算公式相对较简单，同时也能够很好地刻画图像的形状和空间分布特征，因此它被广泛应用于图像分析和处理的各个领域。在 OpenCV 库中，计算图像矩的相关函数包括“moments”、“HuMoments”等等。

目标

在本教程中，您将学习如何：

使用 OpenCV 函数 cv::moments
使用 OpenCV 函数 cv::contourArea
使用 OpenCV 函数 cv::arcLength

C++代码

本教程代码如下所示。您也可以从这里下载

#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
#include <iomanip>
 
using namespace cv;
using namespace std;
 
Mat src_gray;
int thresh = 100;
RNG rng(12345);
 
void thresh_callback(int, void* );
 
int main( int argc, char** argv )
{
 CommandLineParser parser( argc, argv, "{@input | stuff.jpg | input image}" );
 Mat src = imread( samples::findFile( parser.get<String>( "@input" ) ) );
 
 if( src.empty() )
 {
 cout << "Could not open or find the image!\n" << endl;
 cout << "usage: " << argv[0] << " <Input image>" << endl;
 return -1;
 }
 
 cvtColor( src, src_gray, COLOR_BGR2GRAY );
 blur( src_gray, src_gray, Size(3,3) );
 
 const char* source_window = "Source";
 namedWindow( source_window );
 imshow( source_window, src );
 
 const int max_thresh = 255;
 createTrackbar( "Canny thresh:", source_window, &thresh, max_thresh, thresh_callback );
 thresh_callback( 0, 0 );
 
 waitKey();
 return 0;
}
 
void thresh_callback(int, void* )
{
 Mat canny_output;
 Canny( src_gray, canny_output, thresh, thresh*2, 3 );
 vector<vector<Point> > contours;
 findContours( canny_output, contours, RETR_TREE, CHAIN_APPROX_SIMPLE );
 
 vector<Moments> mu(contours.size() );
 for( size_t i = 0; i < contours.size(); i++ )
 {
 mu[i] = moments( contours[i] );
 }
 
 vector<Point2f> mc( contours.size() );
 for( size_t i = 0; i < contours.size(); i++ )
 {
 //add 1e-5 to avoid division by zero
 mc[i] = Point2f( static_cast<float>(mu[i].m10 / (mu[i].m00 + 1e-5)),
 static_cast<float>(mu[i].m01 / (mu[i].m00 + 1e-5)) );
 cout << "mc[" << i << "]=" << mc[i] << endl;
 }
 
 Mat drawing = Mat::zeros( canny_output.size(), CV_8UC3 );
 for( size_t i = 0; i< contours.size(); i++ )
 {
 Scalar color = Scalar( rng.uniform(0, 256), rng.uniform(0,256), rng.uniform(0,256) );
 drawContours( drawing, contours, (int)i, color, 2 );
 circle( drawing, mc[i], 4, color, -1 );
 }
 
 imshow( "Contours", drawing );
 
 cout << "\t Info: Area and Contour Length \n";
 for( size_t i = 0; i < contours.size(); i++ )
 {
 cout << " * Contour[" << i << "] - Area (M_00) = " << std::fixed << std::setprecision(2) << mu[i].m00
 << " - Area OpenCV: " << contourArea(contours[i]) << " - Length: " << arcLength( contours[i], true ) << endl;
 }
}