OpenCV的图像矩(64)

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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 zeromc[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;}
}