サブピクセル精度でのコーナー位置検出

目次

• 目的
• 理論
• コード
• 解説
• 結果

前のチュートリアル: 独自のコーナー検出器を作成する
次のチュートリアル: 特徴検出

原著者	Ana Huamán
互換性	OpenCV >= 3.0

目的

このチュートリアルでは、以下の方法を学ぶ:

• OpenCVの関数 cv::cornerSubPix を用いて、より正確なコーナー位置(整数ピクセルよりも正確)を求める。

理論

コード

C++

このチュートリアルのコードを以下に示す。こちらからダウンロードすることもできる

 
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
 
using namespace cv;
using namespace std;
 
Mat src, src_gray;
 
int maxCorners = 10;
int maxTrackbar = 25;
 
RNG rng(12345);
const char* source_window = "Image";
 
void goodFeaturesToTrack_Demo( int, void* );
 
int main( int argc, char** argv )
{
 CommandLineParser parser( argc, argv, "{@input | pic3.png | input image}" );
    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 );
 
    namedWindow( source_window );
 
    createTrackbar( "Max corners:", source_window, &maxCorners, maxTrackbar, goodFeaturesToTrack_Demo );
 
    imshow( source_window, src );
 
    goodFeaturesToTrack_Demo( 0, 0 );
 
    waitKey();
 return 0;
}
 
void goodFeaturesToTrack_Demo( int, void* )
{
    maxCorners = MAX(maxCorners, 1);
    vector<Point2f> corners;
 double qualityLevel = 0.01;
 double minDistance = 10;
 int blockSize = 3, gradientSize = 3;
 bool useHarrisDetector = false;
 double k = 0.04;
 
 Mat copy = src.clone();
 
    goodFeaturesToTrack( src_gray,
                         corners,
                         maxCorners,
                         qualityLevel,
                         minDistance,
 Mat(),
                         blockSize,
                         gradientSize,
                         useHarrisDetector,
                         k );
 
 
    cout << "** Number of corners detected: " << corners.size() << endl;
 int radius = 4;
 for( size_t i = 0; i < corners.size(); i++ )
    {
        circle( copy, corners[i], radius, Scalar(rng.uniform(0,255), rng.uniform(0, 256), rng.uniform(0, 256)), FILLED );
    }
 
    namedWindow( source_window );
    imshow( source_window, copy );
 
 Size winSize = Size( 5, 5 );
 Size zeroZone = Size( -1, -1 );
 TermCriteria criteria = TermCriteria( TermCriteria::EPS + TermCriteria::COUNT, 40, 0.001 );
 
    cornerSubPix( src_gray, corners, winSize, zeroZone, criteria );
 
 for( size_t i = 0; i < corners.size(); i++ )
    {
        cout << " -- Refined Corner [" << i << "]  (" << corners[i].x << "," << corners[i].y << ")" << endl;
    }
}

Java

このチュートリアルのコードを以下に示す。こちらからダウンロードすることもできる

import java.awt.BorderLayout;
import java.awt.Container;
import java.awt.Image;
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.Point;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.core.TermCriteria;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
 
class CornerSubPix {
 private Mat src = new Mat();
 private Mat srcGray = new Mat();
 private JFrame frame;
 private JLabel imgLabel;
 private static final int MAX_CORNERS = 25;
 private int maxCorners = 10;
 private Random rng = new Random(12345);
 
 public CornerSubPix(String[] args) {
        String filename = args.length > 0 ? args[0] : "../data/pic3.png";
        src = Imgcodecs.imread(filename);
 if (src.empty()) {
            System.err.println("Cannot read image: " + filename);
            System.exit(0);
        }
 
        Imgproc.cvtColor(src, srcGray, Imgproc.COLOR_BGR2GRAY);
 
 // Create and set up the window.
        frame = new JFrame("Shi-Tomasi corner detector demo");
        frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
 // Set up the content pane.
        Image img = HighGui.toBufferedImage(src);
        addComponentsToPane(frame.getContentPane(), img);
 // Use the content pane's default BorderLayout. No need for
 // setLayout(new BorderLayout());
 // Display the window.
        frame.pack();
        frame.setVisible(true);
        update();
    }
 
 private void addComponentsToPane(Container pane, Image img) {
 if (!(pane.getLayout() instanceof BorderLayout)) {
            pane.add(new JLabel("Container doesn't use BorderLayout!"));
 return;
        }
 
        JPanel sliderPanel = new JPanel();
        sliderPanel.setLayout(new BoxLayout(sliderPanel, BoxLayout.PAGE_AXIS));
 
        sliderPanel.add(new JLabel("Max  corners:"));
        JSlider slider = new JSlider(0, MAX_CORNERS, maxCorners);
        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();
                maxCorners = source.getValue();
                update();
            }
        });
        sliderPanel.add(slider);
        pane.add(sliderPanel, BorderLayout.PAGE_START);
 
        imgLabel = new JLabel(new ImageIcon(img));
        pane.add(imgLabel, BorderLayout.CENTER);
    }
 
 private void update() {
        maxCorners = Math.max(maxCorners, 1);
        MatOfPoint corners = new MatOfPoint();
 double qualityLevel = 0.01;
 double minDistance = 10;
 int blockSize = 3, gradientSize = 3;
 boolean useHarrisDetector = false;
 double k = 0.04;
 
        Mat copy = src.clone();
 
        Imgproc.goodFeaturesToTrack(srcGray, corners, maxCorners, qualityLevel, minDistance, new Mat(),
                blockSize, gradientSize, useHarrisDetector, k);
 
        System.out.println("** Number of corners detected: " + corners.rows());
 int[] cornersData = new int[(int) (corners.total() * corners.channels())];
        corners.get(0, 0, cornersData);
 int radius = 4;
        Mat matCorners = new Mat(corners.rows(), 2, CvType.CV_32F);
 float[] matCornersData = new float[(int) (matCorners.total() * matCorners.channels())];
        matCorners.get(0, 0, matCornersData);
 for (int i = 0; i < corners.rows(); i++) {
            Imgproc.circle(copy, new Point(cornersData[i * 2], cornersData[i * 2 + 1]), radius,
 new Scalar(rng.nextInt(256), rng.nextInt(256), rng.nextInt(256)), Imgproc.FILLED);
            matCornersData[i * 2] = cornersData[i * 2];
            matCornersData[i * 2 + 1] = cornersData[i * 2 + 1];
        }
        matCorners.put(0, 0, matCornersData);
 
        imgLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(copy)));
        frame.repaint();
 
 Size winSize = new Size(5, 5);
 Size zeroZone = new Size(-1, -1);
        TermCriteria criteria = new TermCriteria(TermCriteria.EPS + TermCriteria.COUNT, 40, 0.001);
 
        Imgproc.cornerSubPix(srcGray, matCorners, winSize, zeroZone, criteria);
 
        matCorners.get(0, 0, matCornersData);
 for (int i = 0; i < corners.rows(); i++) {
            System.out.println(
 " -- Refined Corner [" + i + "]  (" + matCornersData[i * 2] + "," + matCornersData[i * 2 + 1] + ")");
        }
    }
}
 
public class CornerSubPixDemo {
 public static void main(String[] args) {
 // Load the native OpenCV library
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
 
 // Schedule a job for the event dispatch thread:
 // creating and showing this application's GUI.
        javax.swing.SwingUtilities.invokeLater(new Runnable() {
            @Override
 public void run() {
 new CornerSubPix(args);
            }
        });
    }
}

Python

このチュートリアルのコードを以下に示す。こちらからダウンロードすることもできる

from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse
import random as rng
 
source_window = 'Image'
maxTrackbar = 25
rng.seed(12345)
 
def goodFeaturesToTrack_Demo(val):
    maxCorners = max(val, 1)
 
 # Parameters for Shi-Tomasi algorithm
    qualityLevel = 0.01
    minDistance = 10
    blockSize = 3
    gradientSize = 3
    useHarrisDetector = False
    k = 0.04
 
 # Copy the source image
    copy = np.copy(src)
 
 # Apply corner detection
    corners = cv.goodFeaturesToTrack(src_gray, maxCorners, qualityLevel, minDistance, None, \
        blockSize=blockSize, gradientSize=gradientSize, useHarrisDetector=useHarrisDetector, k=k)
 
 # Draw corners detected
    print('** Number of corners detected:', corners.shape[0])
    radius = 4
 for i in range(corners.shape[0]):
 cv.circle(copy, (int(corners[i,0,0]), int(corners[i,0,1])), radius, (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256)), cv.FILLED)
 
 # Show what you got
 cv.namedWindow(source_window)
 cv.imshow(source_window, copy)
 
 # Set the needed parameters to find the refined corners
    winSize = (5, 5)
    zeroZone = (-1, -1)
    criteria = (cv.TERM_CRITERIA_EPS + cv.TermCriteria_COUNT, 40, 0.001)
 
 # Calculate the refined corner locations
    corners = cv.cornerSubPix(src_gray, corners, winSize, zeroZone, criteria)
 
 # Write them down
 for i in range(corners.shape[0]):
        print(" -- Refined Corner [", i, "]  (", corners[i,0,0], ",", corners[i,0,1], ")")
 
# Load source image and convert it to gray
parser = argparse.ArgumentParser(description='Code for Shi-Tomasi corner detector tutorial.')
parser.add_argument('--input', help='Path to input image.', default='pic3.png')
args = parser.parse_args()
 
src = cv.imread(cv.samples.findFile(args.input))
if src is None:
    print('Could not open or find the image:', args.input)
    exit(0)
 
src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
 
# Create a window and a trackbar
cv.namedWindow(source_window)
maxCorners = 10 # initial threshold
cv.createTrackbar('Threshold: ', source_window, maxCorners, maxTrackbar, goodFeaturesToTrack_Demo)
cv.imshow(source_window, src)
goodFeaturesToTrack_Demo(maxCorners)
 
cv.waitKey()

解説

結果

結果は次のとおり: