javaopencvadaptive-threshold

How to identify the black dot in the image


I did adaptive thresholding with java OpenCV to identify the black dot which is in the image. However I failed to do that.My codes are as follows.Have to detect the black dot in the image When I was following the code which I wrote in here, the code unable to detect the black dot.The output image which is generated from this can be shown as follows. However this is not the image that I need

/*
 * To change this license header, choose License Headers in Project Properties.
 * To change this template file, choose Tools | Templates
 * and open the template in the editor.
 */

/**
 *
 * @author Samarasinghe
 */
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.io.File;
import java.util.ArrayList;
import java.util.List;
import javax.imageio.ImageIO;
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.Rect;
import org.opencv.core.Scalar;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;

public class kkknewversionj extends javax.swing.JFrame {

    /**
     * Creates new form kkknewversionj
     */
    double sum =0;
    public kkknewversionj() {
        initComponents();
    }
    public double imageprocessing1(){
        try{
            System.loadLibrary( Core.NATIVE_LIBRARY_NAME);
            //BufferedImage image= ImageIO.read(new File("C:\\Users\\My Kindom\\Desktop\\printscreen.JPG"));
            BufferedImage image= ImageIO.read(new File("C:\\Users\\Samarasinghe\\Downloads\\IS_11.jpg"));      
            byte[] data =((DataBufferByte) image.getRaster().getDataBuffer()).getData();
                    Mat mat = new Mat(image.getHeight(),image.getWidth(), CvType.CV_8UC3);
                    mat.put(0, 0, data);

                    Mat mat1 = new Mat(image.getHeight(), image.getWidth(), CvType.CV_8UC3);
                    Imgproc.cvtColor(mat, mat1, Imgproc.COLOR_RGB2GRAY);

                    byte[] data1 = new byte[mat1.rows()*mat1.cols()*(int)(mat1.elemSize())];
                    mat1.get(0, 0, data1);
                    BufferedImage image1 = new BufferedImage(mat1.cols(), mat1.rows(),BufferedImage.TYPE_BYTE_GRAY);
                    image1.getRaster().setDataElements(0, 0, mat1.cols(), mat1.rows(), data1);

                    ImageIO.write(image1, "jpg", new File("C:\\Users\\Samarasinghe\\Desktop\\gray.jpg"));
                    Mat source = Imgcodecs.imread("C:\\Users\\Samarasinghe\\Desktop\\gray.jpg",Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);
                    Mat destination = new Mat(source.rows(),source.cols(),source.type());
                    destination = source;

                    Imgproc.adaptiveThreshold(source,destination,255,Imgproc.ADAPTIVE_THRESH_MEAN_C,Imgproc.THRESH_BINARY, 19,-9);
                    Imgcodecs.imwrite("C:\\Users\\Samarasinghe\\Desktop\\ThreshZero.jpg", destination);
                    List<MatOfPoint> contours= new ArrayList<>();
                    Mat hierarchy =new Mat();

                    Imgproc.findContours(destination, contours, hierarchy,Imgproc.RETR_EXTERNAL,Imgproc.CHAIN_APPROX_NONE);
                    //Mat mask= new Mat (image.getHeight(),image.getWidth(),CvType.CV_8UC3);
                    Imgcodecs.imwrite("C:\\Users\\Samarasinghe\\Desktop\\mask.jpg",destination);
                    //Imgproc.drawContours(mask, contours,NORMAL, white);
                    //Imgcodecs.imwrite("C:\\Users\\Samarasinghe\\Desktop\\mask.jpg",mask);

                    for(int j=0;j<contours.size();j++){

                          sum=sum+contours.size();
//                          double[] d= hierarchy.get(0, j);
//                          Rect rect = Imgproc.boundingRect(contours.get(j));
//                          Point pt1=new Point(rect.x,rect.y);
//                          Point pt2=new Point(rect.x+rect.width,rect.y+rect.height);
//                          Scalar  eder=new Scalar(0,255,0);
//                          Imgproc.rectangle(destination, pt1, pt2, eder,2);
//                          Mat contour = contours.get(j);
//                          double contourarea=Imgproc.contourArea(contour);
//                          sum = sum + contourarea;

                    }System.out.println("Sum"+sum);



        }catch(Exception e){

        }
        return sum ;

    };


    /**
     * This method is called from within the constructor to initialize the form.
     * WARNING: Do NOT modify this code. The content of this method is always
     * regenerated by the Form Editor.
     */
    @SuppressWarnings("unchecked")
    // <editor-fold defaultstate="collapsed" desc="Generated Code">                          
    private void initComponents() {

        jButton1 = new javax.swing.JButton();

        setDefaultCloseOperation(javax.swing.WindowConstants.EXIT_ON_CLOSE);

        jButton1.setText("jButton1");
        jButton1.addActionListener(new java.awt.event.ActionListener() {
            public void actionPerformed(java.awt.event.ActionEvent evt) {
                jButton1ActionPerformed(evt);
            }
        });

        javax.swing.GroupLayout layout = new javax.swing.GroupLayout(getContentPane());
        getContentPane().setLayout(layout);
        layout.setHorizontalGroup(
            layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)
            .addGroup(javax.swing.GroupLayout.Alignment.TRAILING, layout.createSequentialGroup()
                .addContainerGap(302, Short.MAX_VALUE)
                .addComponent(jButton1)
                .addGap(25, 25, 25))
        );
        layout.setVerticalGroup(
            layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)
            .addGroup(layout.createSequentialGroup()
                .addGap(89, 89, 89)
                .addComponent(jButton1)
                .addContainerGap(188, Short.MAX_VALUE))
        );

        pack();
    }// </editor-fold>                        

    private void jButton1ActionPerformed(java.awt.event.ActionEvent evt) {                                         
         imageprocessing1();
    }                                        

    /**
     * @param args the command line arguments
     */
    public static void main(String args[]) {
        /* Set the Nimbus look and feel */
        //<editor-fold defaultstate="collapsed" desc=" Look and feel setting code (optional) ">
        /* If Nimbus (introduced in Java SE 6) is not available, stay with the default look and feel.
         * For details see http://download.oracle.com/javase/tutorial/uiswing/lookandfeel/plaf.html 
         */
        try {
            for (javax.swing.UIManager.LookAndFeelInfo info : javax.swing.UIManager.getInstalledLookAndFeels()) {
                if ("Nimbus".equals(info.getName())) {
                    javax.swing.UIManager.setLookAndFeel(info.getClassName());
                    break;
                }
            }
        } catch (ClassNotFoundException ex) {
            java.util.logging.Logger.getLogger(kkknewversionj.class.getName()).log(java.util.logging.Level.SEVERE, null, ex);
        } catch (InstantiationException ex) {
            java.util.logging.Logger.getLogger(kkknewversionj.class.getName()).log(java.util.logging.Level.SEVERE, null, ex);
        } catch (IllegalAccessException ex) {
            java.util.logging.Logger.getLogger(kkknewversionj.class.getName()).log(java.util.logging.Level.SEVERE, null, ex);
        } catch (javax.swing.UnsupportedLookAndFeelException ex) {
            java.util.logging.Logger.getLogger(kkknewversionj.class.getName()).log(java.util.logging.Level.SEVERE, null, ex);
        }
        //</editor-fold>

        /* Create and display the form */
        java.awt.EventQueue.invokeLater(new Runnable() {
            public void run() {
                new kkknewversionj().setVisible(true);
            }
        });
    }

    // Variables declaration - do not modify                     
    private javax.swing.JButton jButton1;
    // End of variables declaration                   
}

Solution

  • Zdar is right in the comments, you should switch color representation. Here, you are thresholding on a graylevel, which in your case is not great since it is hard to distinguish between the blue line and black spot.

    If you represent your image in another color system, for instance one which distinguishes better between "saturated" color and black like HSV, you can segment your black spot much easier.

    Here is the result I got for the Value channel of an HSV representation of your image  the Value channel of an HSV representation of your image.

    If you do not know about color spaces, you can check out the pretty complete Wikipedia article about it, for example : https://en.wikipedia.org/wiki/HSL_and_HSV (which explains why I am careful with the term "saturated")

    Edit by Krishan : his HSV representation This is my HSV image when I conduct the colour segmentation