我使用java OpenCV进行了自适应阈值识别，以识别图像中的黑点。但是我没有这样做，我的代码如下。
当我遵循此处编写的代码时，该代码无法检测到黑点。
/*
* 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
}
最佳答案
Zdar在注释中是正确的，您应该切换颜色表示。
在这里，您需要在灰度级上进行阈值设置，这在您的情况下并不理想，因为很难区分蓝线和黑点。
如果您用另一种颜色系统来表示图像，例如可以更好地区分“饱和”颜色和黑色(如HSV)的图像，则可以更轻松地划分黑点。
这是我为图像的HSV表示形式的Value通道获得的结果。
如果您不了解颜色空间，则可以查看有关它的相当完整的Wikipedia文章，例如:https://en.wikipedia.org/wiki/HSL_and_HSV(这解释了为什么我对术语“饱和”要小心)
克里山(Krishan)编辑:他的HSV表示形式
关于java - 如何识别图像中的黑点，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/41561364/