Shi-Tomasi corner detector#


Original author	Ana Huamán
Compatibility	OpenCV >= 3.0

Goal#

In this tutorial you will learn how to:

Use the function cv::goodFeaturesToTrack to detect corners using the Shi-Tomasi method ([272]).

Theory#

Code#

C++

This tutorial code’s is shown lines below. You can also download it from here

#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/features.hpp"
#include <iostream>

using namespace cv;
using namespace std;

/// Global variables
Mat src, src_gray;

int maxCorners = 23;
int maxTrackbar = 100;

RNG rng(12345);
const char* source_window = "Image";

/// Function header
void goodFeaturesToTrack_Demo( int, void* );

int main( int argc, char** argv )
{
    /// Load source image and convert it to gray
    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 );

    /// Create Window
    namedWindow( source_window );

    /// Create Trackbar to set the number of corners
    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* )
{
    /// Parameters for Shi-Tomasi algorithm
    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;

    /// Copy the source image
    Mat copy = src.clone();

    /// Apply corner detection
    goodFeaturesToTrack( src_gray,
                         corners,
                         maxCorners,
                         qualityLevel,
                         minDistance,
                         Mat(),
                         blockSize,
                         gradientSize,
                         useHarrisDetector,
                         k );

    /// Draw corners detected
    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 );
    }

    /// Show what you got
    namedWindow( source_window );
    imshow( source_window, copy );
}

Java

This tutorial code’s is shown lines below. You can also download it from here

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.Mat;
import org.opencv.core.MatOfPoint;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.features.Features;

class GoodFeaturesToTrack {
    private Mat src = new Mat();
    private Mat srcGray = new Mat();
    private JFrame frame;
    private JLabel imgLabel;
    private static final int MAX_THRESHOLD = 100;
    private int maxCorners = 23;
    private Random rng = new Random(12345);

    public GoodFeaturesToTrack(String[] args) {
        /// Load source image and convert it to gray
        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_THRESHOLD, 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() {
        /// Parameters for Shi-Tomasi algorithm
        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;

        /// Copy the source image
        Mat copy = src.clone();

        /// Apply corner detection
        Features.goodFeaturesToTrack(srcGray, corners, maxCorners, qualityLevel, minDistance, new Mat(),
                blockSize, gradientSize, useHarrisDetector, k);

        /// Draw corners detected
        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;
        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);
        }

        imgLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(copy)));
        frame.repaint();
    }
}

public class GoodFeaturesToTrackDemo {
    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 GoodFeaturesToTrack(args);
            }
        });
    }
}

Python

This tutorial code’s is shown lines below. You can also download it from here

from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse
import random as rng

source_window = 'Image'
maxTrackbar = 100
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)

# 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 = 23 # initial threshold
cv.createTrackbar('Threshold: ', source_window, maxCorners, maxTrackbar, goodFeaturesToTrack_Demo)
cv.imshow(source_window, src)
goodFeaturesToTrack_Demo(maxCorners)

cv.waitKey()

Shi-Tomasi corner detector#

Goal#

Theory#

Code#

Explanation#

Result#