图像矩

目录

• 目标
• 理论
• 代码
• 解释
• 结果

上一篇教程： 为轮廓创建旋转边界框和椭圆
下一篇教程： 点多边形测试

原作者	Ana Huamán
兼容性	OpenCV >= 3.0

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

理论

代码

C++JavaPython

C++

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 << "无法打开或找到图像！\n" << endl;
cout << "用法：" << argv[0] << " <输入图像>" << endl;
        return -1; -1;
    }
 
cvtColor( src, src_gray, COLOR_BGR2GRAY );
blur( src_gray, src_gray, Size(3,3) );
 
    const char* source_window = "源图像";
namedWindow( source_window );
imshow( source_window, src );
 
    const int max_thresh = 255;
createTrackbar( "Canny 阈值:", source_window, &thresh, max_thresh, thresh_callback );
thresh_callback( 0, 0 );
 
waitKey();
    return -1; 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++ )
    {
        //添加 1e-5 以避免除以零
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( "轮廓", drawing );
 
cout << "\t 信息：面积和轮廓长度 \n";
    for( size_t i = 0; i < contours.size(); i++ )
    {
cout << " * 轮廓[" << i << "] - 面积 (M_00) = " << std::fixed << std::setprecision(2) << mu[i].m00
<< " - OpenCV 计算面积: " << contourArea(contours[i]) << " - 长度: " << arcLength( contours[i], true ) << endl;
    }
}

Java

本教程代码如下所示。您也可以从 这里 下载。

import java.awt.BorderLayout;
import java.awt.Container;
import java.awt.Image;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
 
import javax.swing.BoxLayout;
import javax.swing.ImageIcon;
import javax.swing.JFrame;
import javax.swing.JLabel;
import javax.swing.JPanel;
import javax.swing.JSlider;
import javax.swing.event.ChangeEvent;
import javax.swing.event.ChangeListener;
 
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.MatOfPoint;
import org.opencv.core.MatOfPoint2f;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.imgproc.Moments;
 
class MomentsClass {
    private Mat srcGray = new Mat();
    private JFrame frame;
    private JLabel imgSrcLabel;
    private JLabel imgContoursLabel;
    private static final int MAX_THRESHOLD = 255;
    private int threshold = 100;
    private Random rng = new Random(12345);
 
    public MomentsClass(String[] args) {
String filename = args.length > 0 ? args[0] : "../data/stuff.jpg";
Mat src = Imgcodecs.imread(filename);
        if (src.empty()) {
System.err.println("无法读取图像: " + filename);
System.exit(0);
        }
 
Imgproc.cvtColor(src, srcGray, Imgproc.COLOR_BGR2GRAY);
Imgproc.blur(srcGray, srcGray, new Size(3, 3));
 
        // 创建并设置窗口。
frame = new JFrame("图像矩演示");
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        // 设置内容窗格。
Image img = HighGui.toBufferedImage(src);
addComponentsToPane(frame.getContentPane(), img);
        // 使用内容窗格的默认 BorderLayout。无需
        // setLayout(new BorderLayout());
        // 显示窗口。
frame.pack();
frame.setVisible(true);
update();
    }
 
    private void addComponentsToPane(Container pane, Image img) {
        if (!(pane.getLayout() instanceof BorderLayout)) {
pane.add(new JLabel("容器未使用 BorderLayout!"));
            return -1;;
        }
 
JPanel sliderPanel = new JPanel();
sliderPanel.setLayout(new BoxLayout(sliderPanel, BoxLayout.PAGE_AXIS));
 
sliderPanel.add(new JLabel("Canny 阈值: "));
JSlider slider = new JSlider(0, MAX_THRESHOLD, threshold);
slider.setMajorTickSpacing(20);
slider.setMinorTickSpacing(10);
slider.setPaintTicks(true);
slider.setPaintLabels(true);
slider.addChangeListener(new ChangeListener() {
@Override
            public void stateChanged(ChangeEvent e) {
JSlider source = (JSlider) e.getSource();
threshold = source.getValue();
update();
            }
        });
update();
}
 
});
sliderPanel.add(slider);
pane.add(sliderPanel, BorderLayout.PAGE_START);
 
JPanel imgPanel = new JPanel();
imgSrcLabel = new JLabel(new ImageIcon(img));
imgPanel.add(imgSrcLabel);
 
Mat blackImg = Mat.zeros(srcGray.size(), CvType.CV_8U);
    }
 
    imgContoursLabel = new JLabel(new ImageIcon(HighGui.toBufferedImage(blackImg)));
imgPanel.add(imgContoursLabel);
pane.add(imgPanel, BorderLayout.CENTER);
 
}
private void update() {
Mat cannyOutput = new Mat();
 
Imgproc.Canny(srcGray, cannyOutput, threshold, threshold * 2);
        List<MatOfPoint> contours = new ArrayList<>();
Mat hierarchy = new Mat();
        }
 
Imgproc.findContours(cannyOutput, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE);
        List<MatOfPoint> contours = new ArrayList<>();
            //添加 1e-5 以避免除以零
List<Moments> mu = new ArrayList<>(contours.size());
        }
 
for (int i = 0; i < contours.size(); i++) {
        List<MatOfPoint> contours = new ArrayList<>();
            mu.add(Imgproc.moments(contours.get(i)));
List<Point> mc = new ArrayList<>(contours.size());
mc.add(new Point(mu.get(i).m10 / (mu.get(i).m00 + 1e-5), mu.get(i).m01 / (mu.get(i).m00 + 1e-5)));
        }
 
Mat drawing = Mat.zeros(cannyOutput.size(), CvType.CV_8UC3);
Scalar color = new Scalar(rng.nextInt(256), rng.nextInt(256), rng.nextInt(256));
 
Imgproc.drawContours(drawing, contours, i, color, 2);
        List<MatOfPoint> contours = new ArrayList<>();
Imgproc.circle(drawing, mc.get(i), 4, color, -1);
imgContoursLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(drawing)));
frame.repaint();
        }
    }
}
 
System.out.println("\t 信息: 面积和轮廓长度 \n");
    System.out.format(" * 轮廓[%d] - 面积 (M_00) = %.2f - OpenCV面积: %.2f - 长度: %.2f\n", i,
        mu.get(i).m00, Imgproc.contourArea(contours.get(i)),
Imgproc.arcLength(new MatOfPoint2f(contours.get(i).toArray()), true));
 
        }
        }
public class MomentsDemo {
@Override
            public static void main(String[] args) {
                // 加载原生 OpenCV 库
            }
        });
    }
}

Python

本教程代码如下所示。您也可以从 这里 下载。

from __future__ import print_function
from __future__ import division
import cv2 as cv
import numpy as np
import argparse
import random as rng
 
rng.seed(12345)
 
def thresh_callback(val):
threshold = val
 
    
canny_output = cv.Canny(src_gray, threshold, threshold * 2)
    
 
    
contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
    
 
    # 获取矩
mu = [None]*len(contours)
    for i in range(len(contours)):
mu[i] = cv.moments(contours[i])
 
    # 获取质心
mc = [None]*len(contours)
    for i in range(len(contours)):
        # 添加 1e-5 以避免除以零
mc[i] = (mu[i]['m10'] / (mu[i]['m00'] + 1e-5), mu[i]['m01'] / (mu[i]['m00'] + 1e-5))
 
    # 绘制轮廓
    
drawing = np.zeros((canny_output.shape[0], canny_output.shape[1], 3), dtype=np.uint8)
    
    for i in range(len(contours)):
color = (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256))
        cv.drawContours(drawing, contours, i, color, 2)
        cv.circle(drawing, (int(mc[i][0]), int(mc[i][1])), 4, color, -1)
    
 
    
    cv.imshow('Contours', drawing)
    
 
    # 使用矩00计算面积，并与OpenCV函数的结果进行比较
    for i in range(len(contours)):
print(' * 轮廓[%d] - 面积 (M_00) = %.2f - OpenCV面积: %.2f - 长度: %.2f' % (i, mu[i]['m00'], cv.contourArea(contours[i]), cv.arcLength(contours[i], True)))
 
 
parser = argparse.ArgumentParser(description='图像矩教程代码.')
parser.add_argument('--input', help='输入图像路径.', default='stuff.jpg')
args = parser.parse_args()
 
src = cv.imread(cv.samples.findFile(args.input))
如果 src 是 空
print('无法打开或找到图像:', args.input)
exit(0)
 
# 将图像转换为灰度并进行模糊处理
src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
src_gray = cv.blur(src_gray, (3,3))
 
 
 
source_window = '源图像'
cv.namedWindow(source_window)
cv.imshow(source_window, src)
 
max_thresh = 255
thresh = 100 # 初始阈值
cv.createTrackbar('Canny 阈值:', source_window, thresh, max_thresh, thresh_callback)
thresh_callback(thresh)
 
 
cv.waitKey()

说明

结果

结果如下：