OpenCV和Java，光学变换：腐蚀、膨胀、形态学变换、边缘检测

ASR/CV/ML OpenCV和Java，光学变换：腐蚀、膨胀、形态学变换、边缘检测

Imgproc
.Canny
.GaussianBlur
.morphologyEx
腐蚀、膨胀产生类似毛玻璃的模糊效果，类似模糊操作的效果。
形态学变换根据操作方式，再多产生类似反相、轮廓( http://www.gaohaiyan.com/3296.html )的效果。
边缘检测产生黑底白线条的“白描”效果。

import java.awt.Color;
import java.awt.event.ItemEvent;
import java.awt.event.ItemListener;
import java.awt.image.BufferedImage;
import javax.swing.ButtonGroup;
import javax.swing.ImageIcon;
import javax.swing.JCheckBox;
import javax.swing.JFrame;
import javax.swing.JLabel;
import javax.swing.JRadioButton;
import javax.swing.JSlider;
import javax.swing.event.ChangeEvent;
import javax.swing.event.ChangeListener;
import org.opencv.core.Mat;
import org.opencv.core.Size;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;

public class Erosion extends JFrame {

    private JLabel imageView;

    private int pic = 1;
    private int ksize = 1;
    private int shape = 0;
    private int op = 0;
    private double threshold_1 = 0;
    private double threshold_2 = 0;
    private double gaussian = 1;
    private boolean isGaussian = false;

    private Mat srcMat;

    public Erosion(String img) {

        JLabel ksizeLabel = new JLabel("核：" + ksize);
        JLabel shapeLabel = new JLabel("图形：" + shape);
        JLabel opLabel = new JLabel("操作：" + op);
        opLabel.setForeground(Color.RED);
        JSlider ksizeBar = new JSlider(1, 50);
        JSlider shapeBar = new JSlider(0, 2);
        JSlider opBar = new JSlider(0, 7);
        JRadioButton erodeBtn = new JRadioButton("腐蚀");
        erodeBtn.setSelected(true);
        JRadioButton dilateBtn = new JRadioButton("膨胀");
        JRadioButton morphologyBtn = new JRadioButton("形态学变换");
        morphologyBtn.setForeground(Color.RED);
        JRadioButton cannyBtn = new JRadioButton("边缘检测");
        cannyBtn.setForeground(Color.GREEN);
        ButtonGroup group = new ButtonGroup();
        group.add(erodeBtn);
        group.add(dilateBtn);
        group.add(morphologyBtn);
        group.add(cannyBtn);

        ksizeLabel.setBounds(10, 10, 45, 25);
        shapeLabel.setBounds(160, 10, 55, 25);
        opLabel.setBounds(320, 10, 55, 25);
        ksizeBar.setBounds(50, 10, 100, 25);
        shapeBar.setBounds(210, 10, 100, 25);
        opBar.setBounds(370, 10, 100, 25);
        ksizeBar.setValue(1);
        shapeBar.setValue(0);
        opBar.setValue(0);
        erodeBtn.setBounds(10, 40, 65, 25);
        dilateBtn.setBounds(70, 40, 65, 25);
        morphologyBtn.setBounds(130, 40, 100, 25);
        cannyBtn.setBounds(240, 40, 90, 25);

        JLabel threshold_1_Label = new JLabel("临界1：" + 1);
        threshold_1_Label.setBounds(250, 70, 80, 25);
        threshold_1_Label.setForeground(Color.GREEN);
        JSlider threshold_1_Bar = new JSlider(1, 500);
        threshold_1_Bar.setValue(1);
        threshold_1_Bar.setBounds(320, 70, 150, 25);
        JLabel threshold_2_Label = new JLabel("临界2：" + 1);
        threshold_2_Label.setBounds(250, 90, 80, 25);
        threshold_2_Label.setForeground(Color.GREEN);
        JSlider threshold_2_Bar = new JSlider(1, 500);
        threshold_2_Bar.setValue(1);
        threshold_2_Bar.setBounds(320, 90, 150, 25);
        JLabel gaussianLabel = new JLabel("高斯：" + 1);
        gaussianLabel.setBounds(250, 110, 80, 25);
        gaussianLabel.setForeground(Color.GREEN);
        JSlider gaussianBar = new JSlider(1, 50);
        gaussianBar.setValue(1);
        gaussianBar.setBounds(320, 110, 150, 25);

        JCheckBox cannyCheckBox = new JCheckBox("高斯模糊");
        cannyCheckBox.setForeground(Color.GREEN);
        cannyCheckBox.setBounds(470, 110, 90, 25);
        cannyCheckBox.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                isGaussian = !isGaussian;
            }
        });

        ksizeBar.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                ksize = ksizeBar.getValue();
                ksizeLabel.setText("核：" + ksize);
                setPic();
            }
        });
        shapeBar.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                shape = shapeBar.getValue();
                shapeLabel.setText("图形：" + shape);
                setPic();
            }
        });
        opBar.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                op = opBar.getValue();
                opLabel.setText("操作：" + op);
                setPic();
            }
        });
        threshold_1_Bar.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                threshold_1 = threshold_1_Bar.getValue();
                threshold_1_Label.setText("临界1：" + threshold_1);
                setPic();
            }
        });
        threshold_2_Bar.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                threshold_2 = threshold_2_Bar.getValue();
                threshold_2_Label.setText("临界2：" + threshold_2);
                setPic();
            }
        });
        gaussianBar.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                int value = gaussianBar.getValue();
                if (value % 2 == 0) {
                    value = value + 1;
                }
                gaussian = value * 1.0d;
                gaussianLabel.setText("高斯：" + gaussian);
                setPic();
            }
        });

        erodeBtn.addItemListener(new ItemListener() {
            @Override
            public void itemStateChanged(ItemEvent e) {
                pic = 1;
                if (erodeBtn.isSelected()) {
                    ksizeLabel.setForeground(Color.BLACK);
                    shapeLabel.setForeground(Color.BLACK);
                }
            }
        });
        dilateBtn.addItemListener(new ItemListener() {
            @Override
            public void itemStateChanged(ItemEvent e) {
                pic = 2;
                if (dilateBtn.isSelected()) {
                    ksizeLabel.setForeground(Color.BLACK);
                    shapeLabel.setForeground(Color.BLACK);
                }
            }
        });
        morphologyBtn.addItemListener(new ItemListener() {
            @Override
            public void itemStateChanged(ItemEvent e) {
                pic = 3;
                if (morphologyBtn.isSelected()) {
                    ksizeLabel.setForeground(Color.RED);
                    shapeLabel.setForeground(Color.RED);
                }
            }
        });
        cannyBtn.addItemListener(new ItemListener() {
            @Override
            public void itemStateChanged(ItemEvent e) {
                pic = 4;
                if (cannyBtn.isSelected()) {
                    ksizeLabel.setForeground(Color.BLACK);
                    shapeLabel.setForeground(Color.BLACK);
                }
            }
        });

        //IMREAD_UNCHANGED = -1,           // 返回原通道原深度图像
        //IMREAD_GRAYSCALE = 0,            // 返回单通道（灰度），8位图像
        //IMREAD_COLOR = 1,                // 默认。返回三通道，8位图像
        //IMREAD_ANYDEPTH = 2,             // 返回单通道图像。如果原图像深度为16位或32位，则返回原深度；否则转换为8位
        //IMREAD_ANYCOLOR = 4,             // 返回原通道，8位图像。
        //IMREAD_LOAD_GDAL = 8,            // 使用gdal驱动程序加载图像
        //IMREAD_REDUCED_GRAYSCALE_2 = 16, // 返回单通道灰度图像，图像尺寸减小为原来的1/2。
        //IMREAD_REDUCED_COLOR_2 = 17,     // 返回3通道BGR彩色图像，图像尺寸减小为原来的1/2。
        //IMREAD_REDUCED_GRAYSCALE_4 = 32, // 返回单通道灰度图像，图像尺寸减小为原来的1/4
        //IMREAD_REDUCED_COLOR_4 = 33,     // 返回3通道BGR彩色图像，图像尺寸减小为原来的1/4
        //IMREAD_REDUCED_GRAYSCALE_8 = 64, // 返回单通道灰度图像，图像尺寸减小为原来的1/8。
        //IMREAD_REDUCED_COLOR_8 = 65,     // 返回3通道BGR彩色图像，图像尺寸减小为原来的1/8。
        //IMREAD_IGNORE_ORIENTATION = 128; // 返回的图像不会根据EXIF信息的方向标志旋转。
        srcMat = Imgcodecs.imread(img, 1);
        imageView = new JLabel("");
        imageView.setBounds(10, 130, 512, 600);

        this.setTitle("光学变换");
        this.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        this.setSize(600, 640);
        this.getContentPane().setLayout(null);
        this.getContentPane().add(erodeBtn);
        this.getContentPane().add(dilateBtn);
        this.getContentPane().add(morphologyBtn);
        this.getContentPane().add(ksizeLabel);
        this.getContentPane().add(ksizeBar);
        this.getContentPane().add(shapeLabel);
        this.getContentPane().add(shapeBar);
        this.getContentPane().add(opLabel);
        this.getContentPane().add(opBar);
        this.getContentPane().add(cannyBtn);
        this.getContentPane().add(threshold_1_Label);
        this.getContentPane().add(threshold_1_Bar);
        this.getContentPane().add(threshold_2_Label);
        this.getContentPane().add(threshold_2_Bar);
        this.getContentPane().add(gaussianLabel);
        this.getContentPane().add(gaussianBar);
        this.getContentPane().add(cannyCheckBox);
        this.getContentPane().add(imageView);

        setIcon(srcMat);
    }

    private void setPic() {
        // shape取值：
        // Imgproc.MORPH_RECT = 0, 核是3x3像素的矩形
        // Imgproc.MORPH_CROSS = 1, 核是3x3像素的十字
        // Imgproc.MORPH_ELLIPSE = 2; 核是3x3像素的圆
        Mat element = Imgproc.getStructuringElement(shape, new Size(ksize, ksize)); // 结构元素
        Mat dstMat = new Mat(srcMat.rows(), srcMat.cols(), srcMat.type());
        if (1 == pic) { // 腐蚀。用核对像素做卷积，保留最小值
            Imgproc.erode(srcMat, dstMat, element);
        } else if (2 == pic) { // 膨胀。用核对像素做卷积，保留最大值
            Imgproc.dilate(srcMat, dstMat, element);
        } else if (3 == pic) { // 形态学变换
            // op参数：
            //MORPH_ERODE = 0,    // 同腐蚀操作
            //MORPH_DILATE = 1,   // 同膨胀操作
            //MORPH_OPEN = 2,     // 先腐蚀再膨胀
            //MORPH_CLOSE = 3,    // 先膨胀再腐蚀
            //MORPH_GRADIENT = 4, // 膨胀效果 减去 腐蚀效果
            //MORPH_TOPHAT = 5,   // 原图 减去 MORPH_OPEN
            //MORPH_BLACKHAT = 6, // MORPH_CLOSE 减去 原图
            //MORPH_HITMISS = 7;  // 击'中'击'不中'/命中错过，此时须srcMat.type() == CV_8UC1。先用结构元素腐蚀图像，再用结构元素腐蚀图像的补集，最后把前两步结果的与运算
            if (op < 7) {
                Imgproc.morphologyEx(srcMat, dstMat, op, element);
            } else {
                Mat grayMat = new Mat(srcMat.rows(), srcMat.cols(), srcMat.type());
                Imgproc.cvtColor(srcMat, grayMat, Imgproc.COLOR_BGR2GRAY); // 转灰度图
                Imgproc.morphologyEx(grayMat, dstMat, op, element);
            }
        } else if (4 == pic) {
            if (isGaussian) {
                Mat tmpMat = new Mat(srcMat.rows(), srcMat.cols(), srcMat.type());
                Imgproc.GaussianBlur(srcMat, tmpMat, new Size(gaussian, gaussian), 0);
                Imgproc.Canny(tmpMat, dstMat, threshold_1, threshold_2);
            } else {
                Imgproc.Canny(srcMat, dstMat, threshold_1, threshold_2);
            }
        }
        setIcon(dstMat);
    }

    private void setIcon(Mat mat) {
        BufferedImage image = CVUtil.matToBufferedImage(mat); // CVUtil 见 http://www.gaohaiyan.com/3229.html
        imageView.setIcon(new ImageIcon(image));
    }
}

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import java.awt.Color;

import java.awt.event.ItemEvent;

import java.awt.event.ItemListener;

import java.awt.image.BufferedImage;

import javax.swing.ButtonGroup;

import javax.swing.ImageIcon;

import javax.swing.JCheckBox;

import javax.swing.JFrame;

import javax.swing.JLabel;

import javax.swing.JRadioButton;

import javax.swing.JSlider;

import javax.swing.event.ChangeEvent;

import javax.swing.event.ChangeListener;

import org.opencv.core.Mat;

import org.opencv.core.Size;

import org.opencv.imgcodecs.Imgcodecs;

import org.opencv.imgproc.Imgproc;

public class Erosion extends JFrame {

private JLabel imageView;

private int pic = 1;

private int ksize = 1;

private int shape = 0;

private int op = 0;

private double threshold_1 = 0;

private double threshold_2 = 0;

private double gaussian = 1;

private boolean isGaussian = false;

private Mat srcMat;

public Erosion(String img) {

JLabel ksizeLabel = new JLabel("核：" + ksize);

JLabel shapeLabel = new JLabel("图形：" + shape);

JLabel opLabel = new JLabel("操作：" + op);

opLabel.setForeground(Color.RED);

JSlider ksizeBar = new JSlider(1, 50);

JSlider shapeBar = new JSlider(0, 2);

JSlider opBar = new JSlider(0, 7);

JRadioButton erodeBtn = new JRadioButton("腐蚀");

erodeBtn.setSelected(true);

JRadioButton dilateBtn = new JRadioButton("膨胀");

JRadioButton morphologyBtn = new JRadioButton("形态学变换");

morphologyBtn.setForeground(Color.RED);

JRadioButton cannyBtn = new JRadioButton("边缘检测");

cannyBtn.setForeground(Color.GREEN);

ButtonGroup group = new ButtonGroup();

group.add(erodeBtn);

group.add(dilateBtn);

group.add(morphologyBtn);

group.add(cannyBtn);

ksizeLabel.setBounds(10, 10, 45, 25);

shapeLabel.setBounds(160, 10, 55, 25);

opLabel.setBounds(320, 10, 55, 25);

ksizeBar.setBounds(50, 10, 100, 25);

shapeBar.setBounds(210, 10, 100, 25);

opBar.setBounds(370, 10, 100, 25);

ksizeBar.setValue(1);

shapeBar.setValue(0);

opBar.setValue(0);

erodeBtn.setBounds(10, 40, 65, 25);

dilateBtn.setBounds(70, 40, 65, 25);

morphologyBtn.setBounds(130, 40, 100, 25);

cannyBtn.setBounds(240, 40, 90, 25);

JLabel threshold_1_Label = new JLabel("临界1：" + 1);

threshold_1_Label.setBounds(250, 70, 80, 25);

threshold_1_Label.setForeground(Color.GREEN);

JSlider threshold_1_Bar = new JSlider(1, 500);

threshold_1_Bar.setValue(1);

threshold_1_Bar.setBounds(320, 70, 150, 25);

JLabel threshold_2_Label = new JLabel("临界2：" + 1);

threshold_2_Label.setBounds(250, 90, 80, 25);

threshold_2_Label.setForeground(Color.GREEN);

JSlider threshold_2_Bar = new JSlider(1, 500);

threshold_2_Bar.setValue(1);

threshold_2_Bar.setBounds(320, 90, 150, 25);

JLabel gaussianLabel = new JLabel("高斯：" + 1);

gaussianLabel.setBounds(250, 110, 80, 25);

gaussianLabel.setForeground(Color.GREEN);

JSlider gaussianBar = new JSlider(1, 50);

gaussianBar.setValue(1);

gaussianBar.setBounds(320, 110, 150, 25);

JCheckBox cannyCheckBox = new JCheckBox("高斯模糊");

cannyCheckBox.setForeground(Color.GREEN);

cannyCheckBox.setBounds(470, 110, 90, 25);

cannyCheckBox.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

isGaussian = !isGaussian;

}

});

ksizeBar.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

ksize = ksizeBar.getValue();

ksizeLabel.setText("核：" + ksize);

setPic();

}

});

shapeBar.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

shape = shapeBar.getValue();

shapeLabel.setText("图形：" + shape);

setPic();

}

});

opBar.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

op = opBar.getValue();

opLabel.setText("操作：" + op);

setPic();

}

});

threshold_1_Bar.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

threshold_1 = threshold_1_Bar.getValue();

threshold_1_Label.setText("临界1：" + threshold_1);

setPic();

}

});

threshold_2_Bar.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

threshold_2 = threshold_2_Bar.getValue();

threshold_2_Label.setText("临界2：" + threshold_2);

setPic();

}

});

gaussianBar.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

int value = gaussianBar.getValue();

if (value % 2 == 0) {

value = value + 1;

}

gaussian = value * 1.0d;

gaussianLabel.setText("高斯：" + gaussian);

setPic();

}

});

erodeBtn.addItemListener(new ItemListener() {

@Override

public void itemStateChanged(ItemEvent e) {

pic = 1;

if (erodeBtn.isSelected()) {

ksizeLabel.setForeground(Color.BLACK);

shapeLabel.setForeground(Color.BLACK);

}

});

dilateBtn.addItemListener(new ItemListener() {

@Override

public void itemStateChanged(ItemEvent e) {

pic = 2;

if (dilateBtn.isSelected()) {

ksizeLabel.setForeground(Color.BLACK);

shapeLabel.setForeground(Color.BLACK);

}

});

morphologyBtn.addItemListener(new ItemListener() {

@Override

public void itemStateChanged(ItemEvent e) {

pic = 3;

if (morphologyBtn.isSelected()) {

ksizeLabel.setForeground(Color.RED);

shapeLabel.setForeground(Color.RED);

}

});

cannyBtn.addItemListener(new ItemListener() {

@Override

public void itemStateChanged(ItemEvent e) {

pic = 4;

if (cannyBtn.isSelected()) {

ksizeLabel.setForeground(Color.BLACK);

shapeLabel.setForeground(Color.BLACK);

}

});

//IMREAD_UNCHANGED = -1, // 返回原通道原深度图像

//IMREAD_GRAYSCALE = 0, // 返回单通道（灰度），8位图像

//IMREAD_COLOR = 1, // 默认。返回三通道，8位图像

//IMREAD_ANYDEPTH = 2, // 返回单通道图像。如果原图像深度为16位或32位，则返回原深度；否则转换为8位

//IMREAD_ANYCOLOR = 4, // 返回原通道，8位图像。

//IMREAD_LOAD_GDAL = 8, // 使用gdal驱动程序加载图像

//IMREAD_REDUCED_GRAYSCALE_2 = 16, // 返回单通道灰度图像，图像尺寸减小为原来的1/2。

//IMREAD_REDUCED_COLOR_2 = 17, // 返回3通道BGR彩色图像，图像尺寸减小为原来的1/2。

//IMREAD_REDUCED_GRAYSCALE_4 = 32, // 返回单通道灰度图像，图像尺寸减小为原来的1/4

//IMREAD_REDUCED_COLOR_4 = 33, // 返回3通道BGR彩色图像，图像尺寸减小为原来的1/4

//IMREAD_REDUCED_GRAYSCALE_8 = 64, // 返回单通道灰度图像，图像尺寸减小为原来的1/8。

//IMREAD_REDUCED_COLOR_8 = 65, // 返回3通道BGR彩色图像，图像尺寸减小为原来的1/8。

//IMREAD_IGNORE_ORIENTATION = 128; // 返回的图像不会根据EXIF信息的方向标志旋转。

srcMat = Imgcodecs.imread(img, 1);

imageView = new JLabel("");

imageView.setBounds(10, 130, 512, 600);

this.setTitle("光学变换");

this.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);

this.setSize(600, 640);

this.getContentPane().setLayout(null);

this.getContentPane().add(erodeBtn);

this.getContentPane().add(dilateBtn);

this.getContentPane().add(morphologyBtn);

this.getContentPane().add(ksizeLabel);

this.getContentPane().add(ksizeBar);

this.getContentPane().add(shapeLabel);

this.getContentPane().add(shapeBar);

this.getContentPane().add(opLabel);

this.getContentPane().add(opBar);

this.getContentPane().add(cannyBtn);

this.getContentPane().add(threshold_1_Label);

this.getContentPane().add(threshold_1_Bar);

this.getContentPane().add(threshold_2_Label);

this.getContentPane().add(threshold_2_Bar);

this.getContentPane().add(gaussianLabel);

this.getContentPane().add(gaussianBar);

this.getContentPane().add(cannyCheckBox);

this.getContentPane().add(imageView);

setIcon(srcMat);

}

private void setPic() {

// shape取值：

// Imgproc.MORPH_RECT = 0, 核是3x3像素的矩形

// Imgproc.MORPH_CROSS = 1, 核是3x3像素的十字

// Imgproc.MORPH_ELLIPSE = 2; 核是3x3像素的圆

Mat element = Imgproc.getStructuringElement(shape, new Size(ksize, ksize)); // 结构元素

Mat dstMat = new Mat(srcMat.rows(), srcMat.cols(), srcMat.type());

if (1 == pic) { // 腐蚀。用核对像素做卷积，保留最小值

Imgproc.erode(srcMat, dstMat, element);

} else if (2 == pic) { // 膨胀。用核对像素做卷积，保留最大值

Imgproc.dilate(srcMat, dstMat, element);

} else if (3 == pic) { // 形态学变换

// op参数：

//MORPH_ERODE = 0, // 同腐蚀操作

//MORPH_DILATE = 1, // 同膨胀操作

//MORPH_OPEN = 2, // 先腐蚀再膨胀

//MORPH_CLOSE = 3, // 先膨胀再腐蚀

//MORPH_GRADIENT = 4, // 膨胀效果减去腐蚀效果

//MORPH_TOPHAT = 5, // 原图减去 MORPH_OPEN

//MORPH_BLACKHAT = 6, // MORPH_CLOSE 减去原图

//MORPH_HITMISS = 7; // 击'中'击'不中'/命中错过，此时须srcMat.type() == CV_8UC1。先用结构元素腐蚀图像，再用结构元素腐蚀图像的补集，最后把前两步结果的与运算

if (op < 7) {

Imgproc.morphologyEx(srcMat, dstMat, op, element);

} else {

Mat grayMat = new Mat(srcMat.rows(), srcMat.cols(), srcMat.type());

Imgproc.cvtColor(srcMat, grayMat, Imgproc.COLOR_BGR2GRAY); // 转灰度图

Imgproc.morphologyEx(grayMat, dstMat, op, element);

}

} else if (4 == pic) {

if (isGaussian) {

Mat tmpMat = new Mat(srcMat.rows(), srcMat.cols(), srcMat.type());

Imgproc.GaussianBlur(srcMat, tmpMat, new Size(gaussian, gaussian), 0);

Imgproc.Canny(tmpMat, dstMat, threshold_1, threshold_2);

} else {

Imgproc.Canny(srcMat, dstMat, threshold_1, threshold_2);

}

setIcon(dstMat);

}

private void setIcon(Mat mat) {

BufferedImage image = CVUtil.matToBufferedImage(mat); // CVUtil 见 http://www.gaohaiyan.com/3229.html

imageView.setIcon(new ImageIcon(image));

}

关于分水岭算法的图像分割，下图来自 https://www.cnblogs.com/long5683/p/9692845.html ，

下面代码效果：

// 分水岭算法
Mat grayMat = new Mat(srcMat.rows(), srcMat.cols(), CvType.CV_8UC1);
Mat zeroMat = Mat.zeros(grayMat.rows(), grayMat.cols(), CvType.CV_8UC1);
Mat foregroundMat = Mat.zeros(srcMat.rows(), srcMat.cols(), CvType.CV_8UC1);
Mat backgroundMat = Mat.zeros(srcMat.rows(), srcMat.cols(), CvType.CV_8UC1);
Mat markMat = new Mat(zeroMat.size(), CvType.CV_8U, new Scalar(0));
Mat tmp1Mat = new Mat(zeroMat.size(), CvType.CV_8U, new Scalar(0));
Mat tmp2Mat = new Mat(zeroMat.size(), CvType.CV_8U, new Scalar(0));
Mat tmp3Mat = new Mat(zeroMat.size(), CvType.CV_8U, new Scalar(0));

Imgproc.cvtColor(srcMat, grayMat, Imgproc.COLOR_BGR2GRAY);
Imgproc.threshold(grayMat, zeroMat, 100, 255, Imgproc.THRESH_BINARY);     // 二值化，转灰度图。黑白二值
Imgproc.erode(zeroMat, foregroundMat, new Mat(), new Point(-1, -1), 2);  // 腐蚀
Imgproc.dilate(zeroMat, backgroundMat, new Mat(), new Point(-1, -1), 3); // 膨胀
Imgproc.threshold(backgroundMat, backgroundMat, 1, 128, Imgproc.THRESH_BINARY_INV); // 二值化，黑白二值反转
Core.add(foregroundMat, backgroundMat, markMat); // 两值相加

markMat.convertTo(tmp1Mat, CvType.CV_32S); // 转换类型
Imgproc.watershed(srcMat, tmp1Mat);       // 分水岭算法处理
tmp1Mat.convertTo(tmp2Mat, CvType.CV_8U); // 转换类型
tmp1Mat.convertTo(tmp3Mat, CvType.CV_8U, 255, 255); // 转换类型

// setIcon(tmp2Mat);
setIcon(tmp3Mat);

// 分水岭算法

Mat grayMat = new Mat(srcMat.rows(), srcMat.cols(), CvType.CV_8UC1);

Mat zeroMat = Mat.zeros(grayMat.rows(), grayMat.cols(), CvType.CV_8UC1);

Mat foregroundMat = Mat.zeros(srcMat.rows(), srcMat.cols(), CvType.CV_8UC1);

Mat backgroundMat = Mat.zeros(srcMat.rows(), srcMat.cols(), CvType.CV_8UC1);

Mat markMat = new Mat(zeroMat.size(), CvType.CV_8U, new Scalar(0));

Mat tmp1Mat = new Mat(zeroMat.size(), CvType.CV_8U, new Scalar(0));

Mat tmp2Mat = new Mat(zeroMat.size(), CvType.CV_8U, new Scalar(0));

Mat tmp3Mat = new Mat(zeroMat.size(), CvType.CV_8U, new Scalar(0));

Imgproc.cvtColor(srcMat, grayMat, Imgproc.COLOR_BGR2GRAY);

Imgproc.threshold(grayMat, zeroMat, 100, 255, Imgproc.THRESH_BINARY); // 二值化，转灰度图。黑白二值

Imgproc.erode(zeroMat, foregroundMat, new Mat(), new Point(-1, -1), 2); // 腐蚀

Imgproc.dilate(zeroMat, backgroundMat, new Mat(), new Point(-1, -1), 3); // 膨胀

Imgproc.threshold(backgroundMat, backgroundMat, 1, 128, Imgproc.THRESH_BINARY_INV); // 二值化，黑白二值反转

Core.add(foregroundMat, backgroundMat, markMat); // 两值相加

markMat.convertTo(tmp1Mat, CvType.CV_32S); // 转换类型

Imgproc.watershed(srcMat, tmp1Mat); // 分水岭算法处理

tmp1Mat.convertTo(tmp2Mat, CvType.CV_8U); // 转换类型

tmp1Mat.convertTo(tmp3Mat, CvType.CV_8U, 255, 255); // 转换类型

// setIcon(tmp2Mat);

setIcon(tmp3Mat);

- end

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