图像处理之简单综合实例(大米计数)

图像处理之简单综合实例(大米计数)

一位网友给我发了几张灰度图像，说是他们单位的工业相机拍摄的，画质非常的清楚，他们

单位是农业科研单位，特别想知道种子的数量，他想知道的是每次工业相机拍摄种子图片中

有多少颗粒种子，想到了用图像处理的办法解决他们的问题，看了他给我照片，以大米种子

为例。实现了一个简单的算法流程，可以得到种子的数目。

大致算法分为以下三个步骤：

1.将灰度图像二值化，二值化方法可以参考以前的文章，求取像素平均值，灰度直方图都

可以

2.去掉二值化以后的图像中干扰噪声。

3.得到种子数目，用彩色标记出来。

源图像如下：

程序处理中间结果及最终效果如下：

二值化处理参见以前的文章 -http://blog.csdn.net/jia20003/article/details/7392325

大米计数与噪声块消去算法基于连通组件标记算法，源代码如下：

package com.gloomyfish.rice.analysis;

import java.awt.image.BufferedImage;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;

import com.gloomyfish.face.detection.AbstractBufferedImageOp;
import com.gloomyfish.face.detection.FastConnectedComponentLabelAlg;

public class FindRiceFilter extends AbstractBufferedImageOp {
	
	private int sumRice;
	
	public int getSumRice() {
		return this.sumRice;
	}

	@Override
	public BufferedImage filter(BufferedImage src, BufferedImage dest) {
		int width = src.getWidth();
        int height = src.getHeight();

        if ( dest == null )
            dest = createCompatibleDestImage( src, null );

        int[] inPixels = new int[width*height];
        int[] outPixels = new int[width*height];
        getRGB(src, 0, 0, width, height, inPixels );
        
		FastConnectedComponentLabelAlg fccAlg = new FastConnectedComponentLabelAlg();
		fccAlg.setBgColor(0);
		int[] outData = fccAlg.doLabel(inPixels, width, height);
		// labels statistic
		HashMap labelMap = new HashMap();
		for(int d=0; d listKeys = new ArrayList();
		for(Integer key : keys) {
			if(labelMap.get(key) <=threshold){
				listKeys.add(key);
			}
			System.out.println( "Number of " + key + " = " + labelMap.get(key));
		}
		sumRice = keys.length - listKeys.size();
		
        // calculate means of pixel  
        int index = 0;    
        for(int row=0; row> 24) & 0xff;  
                tr = (inPixels[index] >> 16) & 0xff;  
                tg = (inPixels[index] >> 8) & 0xff;  
                tb = inPixels[index] & 0xff;
                if(outData[index] != 0 && validRice(outData[index], listKeys)) {
                	tr = tg = tb = 255;
                } else {
                	tr = tg = tb = 0;
                }
                outPixels[index] = (ta << 24) | (tr << 16) | (tg << 8) | tb;
            }
        }
        setRGB( dest, 0, 0, width, height, outPixels );
        return dest;
	}

	private boolean validRice(int i, ArrayList listKeys) {
		for(Integer key : listKeys) {
			if(key == i) {
				return false;
			}
		}
		return true;
	}

}

大米着色处理很简单，只是简单RGB固定着色，源码如下：

package com.gloomyfish.rice.analysis;

import java.awt.image.BufferedImage;

import com.gloomyfish.face.detection.AbstractBufferedImageOp;

public class ColorfulRiceFilter extends AbstractBufferedImageOp {

	@Override
	public BufferedImage filter(BufferedImage src, BufferedImage dest) {
		int width = src.getWidth();
        int height = src.getHeight();

        if ( dest == null )
            dest = createCompatibleDestImage( src, null );

        int[] inPixels = new int[width*height];
        int[] outPixels = new int[width*height];
        getRGB(src, 0, 0, width, height, inPixels );
        
        int index = 0, srcrgb;
        for(int row=0; row> 24) & 0xff;  
//                tr = (inPixels[index] >> 16) & 0xff;  
//                tg = (inPixels[index] >> 8) & 0xff;  
//                tb = inPixels[index] & 0xff;  
            	srcrgb = inPixels[index] & 0x000000ff;
            	if(srcrgb > 0 && row < 140) {
            		tr = 0;
            		tg = 255;
            		tb = 0;
            	} else if(srcrgb > 0 && row >= 140 && row <=280) {
            		tr = 0;
            		tg = 0;
            		tb = 255;
            	} else if(srcrgb > 0 && row >=280) {
            		tr = 255;
            		tg = 0;
            		tb = 0;
            	}
            	else {
            		tr = tg = tb = 0;
            	}
            	outPixels[index] = (ta << 24) | (tr << 16) | (tg << 8) | tb;
            }
        }
        setRGB( dest, 0, 0, width, height, outPixels );
        return dest;
	}
}

测试程序UI代码如下：

package com.gloomyfish.rice.analysis;

import java.awt.BorderLayout;
import java.awt.Color;
import java.awt.Dimension;
import java.awt.FlowLayout;
import java.awt.Graphics;
import java.awt.Graphics2D;
import java.awt.Image;
import java.awt.MediaTracker;
import java.awt.event.ActionEvent;
import java.awt.event.ActionListener;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;

import javax.imageio.ImageIO;
import javax.swing.JButton;
import javax.swing.JComponent;
import javax.swing.JFileChooser;
import javax.swing.JFrame;
import javax.swing.JPanel;

public class MainFrame extends JComponent implements ActionListener {
	/**
	 * 
	 */
	private static final long serialVersionUID = 1518574788794973574L;
	public final static String BROWSE_CMD = "Browse...";
	public final static String NOISE_CMD = "Remove Noise";
	public final static String FUN_CMD = "Colorful Rice";
	
	private BufferedImage rawImg;
	private BufferedImage resultImage;
	private MediaTracker tracker;
	private Dimension mySize;
	
	// JButtons
	private JButton browseBtn;
	private JButton noiseBtn;
	private JButton colorfulBtn;

	// rice number....
	private int riceNum = -1;
	
	
	public MainFrame() {
		JPanel btnPanel = new JPanel();
		btnPanel.setLayout(new FlowLayout(FlowLayout.LEFT));
		browseBtn = new JButton("Browse...");
		noiseBtn = new JButton("Remove Noise");
		colorfulBtn = new JButton("Colorful Rice");
		
		browseBtn.setToolTipText("Please select image file...");
		noiseBtn.setToolTipText("find connected region and draw red rectangle");
		colorfulBtn.setToolTipText("Remove the minor noise region pixels...");
		
		// buttons
		btnPanel.add(browseBtn);
		btnPanel.add(noiseBtn);
		btnPanel.add(colorfulBtn);
		
		// setup listener...
		browseBtn.addActionListener(this);
		noiseBtn.addActionListener(this);
		colorfulBtn.addActionListener(this);
		
		browseBtn.setEnabled(true);
		noiseBtn.setEnabled(true);
		colorfulBtn.setEnabled(true);
		
//		minX = minY =  10000;
//		maxX = maxY = -1;
		
		mySize = new Dimension(500, 300);
		JFrame demoUI = new JFrame("Rice Detection Demo");
		demoUI.getContentPane().setLayout(new BorderLayout());
		demoUI.getContentPane().add(this, BorderLayout.CENTER);
		demoUI.getContentPane().add(btnPanel, BorderLayout.SOUTH);
		demoUI.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
		demoUI.pack();
		demoUI.setVisible(true);
	}
	
	public void paint(Graphics g) {
		Graphics2D g2 = (Graphics2D) g;
		if(rawImg != null) {
			Image scaledImage = rawImg.getScaledInstance(200, 200, Image.SCALE_FAST);
			g2.drawImage(scaledImage, 0, 0, 200, 200, null);
		}
		if(resultImage != null) {
			Image scaledImage = resultImage.getScaledInstance(200, 200, Image.SCALE_FAST);
			g2.drawImage(scaledImage, 210, 0, 200, 200, null);
		}
		
		g2.setPaint(Color.RED);
		if(riceNum > 0) {
			g2.drawString("Number of Rice : " + riceNum, 100, 300);
		} else {
			g2.drawString("Number of Rice : Unknown", 100, 300);
		}
	}
	public Dimension getPreferredSize() {
		return mySize;
	}
	
	public Dimension getMinimumSize() {
		return mySize;
	}
	
	public Dimension getMaximumSize() {
		return mySize;
	}
	
	public static void main(String[] args) {
		new MainFrame();
	}
	
	@Override
	public void actionPerformed(ActionEvent e) {
		if(BROWSE_CMD.equals(e.getActionCommand())) {
			JFileChooser chooser = new JFileChooser();
			chooser.showOpenDialog(null);
			File f = chooser.getSelectedFile();
			BufferedImage bImage = null;
			if(f == null) return;
			try {
				bImage = ImageIO.read(f);
				
			} catch (IOException e1) {
				e1.printStackTrace();
			}
			
			tracker = new MediaTracker(this);
			tracker.addImage(bImage, 1);
			
			// blocked 10 seconds to load the image data
			try {
				if (!tracker.waitForID(1, 10000)) {
					System.out.println("Load error.");
					System.exit(1);
				}// end if
			} catch (InterruptedException ine) {
				ine.printStackTrace();
				System.exit(1);
			} // end catch
			BinaryFilter bfilter = new BinaryFilter();
			rawImg = bfilter.filter(bImage, null);
			repaint();
		} else if(NOISE_CMD.equals(e.getActionCommand())) {
			FindRiceFilter frFilter = new FindRiceFilter();
			resultImage = frFilter.filter(rawImg, null);
			riceNum = frFilter.getSumRice();
			repaint();
		} else if(FUN_CMD.equals(e.getActionCommand())) {
			ColorfulRiceFilter cFilter = new ColorfulRiceFilter();
			resultImage = cFilter.filter(resultImage, null);
			repaint();
		} else {
			// do nothing...
		}
		
	}
}

关于连通组件标记算法，我实现一个优化过的快速版本，可以参见

http://blog.csdn.net/jia20003/article/details/7596443