本文介绍了如何使用opencv java识别黑色的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我正在进行图像处理以识别由石英样品组成的铁颗粒，为此，我必须识别浅灰色背景中的黑色斑点。我建立了一个java程序来做到这一点。然而，该程序没有识别图像中的黑点。请帮帮我。
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*要更改此模板文件，请选择工具|模板
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包图像处理;
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;
/ **
*
* @author My Kindom
* /
公共类imageprocessingf扩展javax.swing.JFrame {
/ **
*创建新表格imageprocessingf
* /
double sum = 0;
public imageprocessingf（）{
initComponents（）;
}
public double imageprocessing1（）{
try {
System.loadLibrary（Core.NATIVE_LIBRARY_NAME）;
// BufferedImage image = ImageIO.read（新文件（C：\\Users \\ Myy Kindom \\Desktop \\printscreen.JPG））;
BufferedImage image = ImageIO.read（新文件（C：\\Users \\Samarasinghe \\Downloads\\IS_1.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_RGB2HSV）;
byte [] data1 = new byte [mat1.rows（）* mat1.cols（）*（int）（mat1.elemSize（））];
mat1.get（0,0，data1）;
BufferedImage image1 = new BufferedImage（mat1.cols（），mat1.rows（），5）;
image1.getRaster（）。setDataElements（0,0，mat1.cols（），mat1.rows（），data1）;
ImageIO.write（image1，jpg，新文件（C：\\Users \\Samarasinghe \\Desktop\\\\\\\\\\\\\\
Mat source = Imgcodecs.imread（C：\\Users \\Samarasinghe\\Desktop\\hsv.jpg，Imgcodecs.CV_LOAD_IMAGE_COLOR）;
Mat destination = new Mat（source.rows（），source.cols（），source.type（））;
destination = source;
标量lowerb =新标量（0,0,0）;
Scalar upperb = new Scalar（180,255,30）;
Core.inRange（source，lowerb，upperb，destination）;
Imgcodecs.imwrite（C：\\Users\\Samarasinghe \\Desktop\\ThreshZero.jpg，目的地）;
列表< MatOfPoint> contours = new ArrayList<>（）;
Mat hierarchy = new Mat（）;
Imgproc.findContours（目的地，等高线，层次结构，Imgproc.RETR_EXTERNAL，Imgproc.CHAIN_APPROX_SIMPLE）;
for（int j = 0; j< contours.size（）; j ++）{
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（例外e）{
}
返还金额;
};
/ **
*从构造函数中调用此方法以初始化表单。
*警告：请勿修改此代码。此方法的内容始终由表单编辑器重新生成
*。
* /
@SuppressWarnings（unchecked）
//< editor-fold defaultstate =collapseddesc =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（272，Short.MAX_VALUE）
.addComponent（jButton1）
.addGap（55,55,55））
）;
layout.setVerticalGroup（
layout.createParallelGroup（javax.swing.GroupLayout.Alignment.LEADING）
.addGroup（javax.swing.GroupLayout.Alignment.TRAILING，layout.createSequentialGroup（）
.addContainerGap（164，Short.MAX_VALUE）
.addComponent（jButton1）
.addGap（113,113,113））
）;
pack（）;
} //< / editor-fold>
private void jButton1ActionPerformed（java.awt.event.ActionEvent evt）{
imageprocessing1（）;
}
/ **
* @param args命令行参数
* /
public static void main（String args []）{
/ *设置Nimbus外观* /
//< editor-fold defaultstate =collapseddesc =外观设置代码（可选）>
/ *如果Nimbus（在Java SE 6中引入）不可用，请使用默认的外观。
*有关详细信息，请参阅http://download.oracle.com/javase/tutorial/uiswing/lookandfeel/plaf.html
* /
尝试{
for（javax.swing） .UIManager.LookAndFeelInfo info：javax.swing.UIManager.getInstalledLookAndFeels（））{
if（Nimbus.equals（info.getName（）））{
javax.swing.UIManager.setLookAndFeel（info .getClassName（））;
休息;
}
}
} catch（ClassNotFoundException ex）{
java.util.logging.Logger.getLogger（imageprocessingf.class.getName（））。log（java.util。 logging.Level.SEVERE，null，ex）;
} catch（InstantiationException ex）{
java.util.logging.Logger.getLogger（imageprocessingf.class.getName（））。log（java.util.logging.Level.SEVERE，null，ex） ;
} catch（IllegalAccessException ex）{
java.util.logging.Logger.getLogger（imageprocessingf.class.getName（））。log（java.util.logging.Level.SEVERE，null，ex） ;
} catch（javax.swing.UnsupportedLookAndFeelException ex）{
java.util.logging.Logger.getLogger（imageprocessingf.class.getName（））。log（java.util.logging.Level.SEVERE， null，ex）;
}
//< / editor-fold>
/ *创建并显示表单* /
java.awt.EventQueue.invokeLater（new Runnable（）{
public void run（）{
new imageprocessingf（）。setVisible （true）;
}
}）;
}
//变量声明 - 不要修改
private javax.swing.JButton jButton1;
//变量结束声明
}
解决方案
我猜您的图像在背景中有一些阴影，全局阈值不会给出预期的结果！
您可以尝试使用自适应阈值或
黑帽：
I am doing image processing to identify the iron particles which are consists on a quartz sample and to do that I have to identify black colour spots which are in light gray background. I built up a java program to do this. However the program did not identify black spots in image. Please help me on this.
/*
* 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.
*/
package imageprocessing;
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;
/**
*
* @author My Kindom
*/
public class imageprocessingf extends javax.swing.JFrame {
/**
* Creates new form imageprocessingf
*/
double sum =0;
public imageprocessingf() {
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_1.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_RGB2HSV);
byte[] data1 = new byte[mat1.rows()*mat1.cols()*(int)(mat1.elemSize())];
mat1.get(0, 0, data1);
BufferedImage image1 = new BufferedImage(mat1.cols(), mat1.rows(), 5);
image1.getRaster().setDataElements(0, 0, mat1.cols(), mat1.rows(), data1);
ImageIO.write(image1, "jpg", new File("C:\\Users\\Samarasinghe\\Desktop\\hsv.jpg"));
Mat source = Imgcodecs.imread("C:\\Users\\Samarasinghe\\Desktop\\hsv.jpg",Imgcodecs.CV_LOAD_IMAGE_COLOR);
Mat destination = new Mat(source.rows(),source.cols(),source.type());
destination = source;
Scalar lowerb=new Scalar (0,0,0);
Scalar upperb=new Scalar (180,255,30);
Core.inRange(source, lowerb, upperb, destination);
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_SIMPLE);
for(int j=0;j<contours.size();j++){
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(272, Short.MAX_VALUE)
.addComponent(jButton1)
.addGap(55, 55, 55))
);
layout.setVerticalGroup(
layout.createParallelGroup(javax.swing.GroupLayout.Alignment.LEADING)
.addGroup(javax.swing.GroupLayout.Alignment.TRAILING, layout.createSequentialGroup()
.addContainerGap(164, Short.MAX_VALUE)
.addComponent(jButton1)
.addGap(113, 113, 113))
);
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(imageprocessingf.class.getName()).log(java.util.logging.Level.SEVERE, null, ex);
} catch (InstantiationException ex) {
java.util.logging.Logger.getLogger(imageprocessingf.class.getName()).log(java.util.logging.Level.SEVERE, null, ex);
} catch (IllegalAccessException ex) {
java.util.logging.Logger.getLogger(imageprocessingf.class.getName()).log(java.util.logging.Level.SEVERE, null, ex);
} catch (javax.swing.UnsupportedLookAndFeelException ex) {
java.util.logging.Logger.getLogger(imageprocessingf.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 imageprocessingf().setVisible(true);
}
});
}
// Variables declaration - do not modify
private javax.swing.JButton jButton1;
// End of variables declaration
}
解决方案
I guess your images have some shading in the background and a global threshold would not give the intended results!
You can try to use an adaptive threshold or a top/bottom-hat transformation + a global threshold to segment the particles. So load your image as grayscale forget about Imgproc.cvtColorand replace Core.InRange with your segmentation method like threshold, adaptiveThreshold or others ;)
Here is some sample code in c++:
//Binarization using fixed threshold -> failed because of shading background
threshold(source,otsu, 0, max_value, THRESH_OTSU);
//Adaptive threshold
adaptiveThreshold(source, adaptive, 255, ADAPTIVE_THRESH_MEAN_C,CV_THRESH_BINARY, 25, 11);
//Segmentation with Black-Hat to uniform background
int const morph_size = 20;
Mat element = getStructuringElement(CV_SHAPE_ELLIPSE, Size(2 * morph_size + 1, 2 * morph_size + 1), Point(morph_size, morph_size));
morphologyEx(source, morph, MORPH_BLACKHAT, element);
threshold(morph, destination, 16, 255, THRESH_BINARY_INV);
Otsu:Adaptive:Black-Hat:
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