OpenCV和Java，图片滤镜、平滑、浮雕、边缘检测

ASR/CV/ML OpenCV和Java，图片滤镜、平滑、浮雕、边缘检测

Imgproc.filter2D
Imgproc.Laplacian
Imgproc.Sobel

卷积运算。

import java.awt.image.BufferedImage;
import javax.swing.ImageIcon;
import javax.swing.JCheckBox;
import javax.swing.JFrame;
import javax.swing.JLabel;
import javax.swing.JSlider;
import javax.swing.event.ChangeEvent;
import javax.swing.event.ChangeListener;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;

/**
 * 图片滤镜、平滑、浮雕、边缘检测
 */
public class Filter extends JFrame {

    private JLabel imageView;

    private int smooth = 1;
    private int sobelX = 1;
    private int sobelY = 1;

    private Mat srcMat;

    public Filter(String img) {

        JLabel smoothLabel = new JLabel("平滑:" + smooth);
        smoothLabel.setBounds(15, 10, 50, 25);
        JSlider smoothBar = new JSlider(1, 10);
        smoothBar.setValue(smooth);
        smoothBar.setBounds(65, 10, 150, 25);
        smoothBar.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                smooth = smoothBar.getValue();
                smoothLabel.setText("平滑:" + smooth);
                smoothPic();
            }
        });

        JCheckBox prewittHBtn = new JCheckBox("水平浮雕");
        prewittHBtn.setBounds(10, 40, 90, 25);
        prewittHBtn.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                prewittHPic(prewittHBtn.isSelected());
            }
        });

        JCheckBox prewittVBtn = new JCheckBox("垂直浮雕");
        prewittVBtn.setBounds(130, 40, 90, 25);
        prewittVBtn.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                prewittVPic(prewittVBtn.isSelected());
            }
        });

        JCheckBox laplacianBtn = new JCheckBox("拉普拉斯边缘检测");
        laplacianBtn.setBounds(10, 70, 160, 25);
        laplacianBtn.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                laplacianPic(laplacianBtn.isSelected());
            }
        });

        JLabel sobelXLabel = new JLabel("索贝尔边缘检测： x=" + sobelX);
        sobelXLabel.setBounds(10, 100, 140, 25);
        JSlider sobelXBar = new JSlider(1, 2);
        sobelXBar.setValue(1);
        sobelXBar.setBounds(140, 100, 150, 25);
        sobelXBar.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                sobelX = sobelXBar.getValue();
                sobelXLabel.setText("索贝尔边缘检测： x=" + sobelX);
                sobelPic();
            }
        }); 
        JLabel sobelYLabel = new JLabel("y=" + sobelY);
        sobelYLabel.setBounds(300, 100, 40, 25);
        JSlider sobelYBar = new JSlider(1, 2);
        sobelYBar.setValue(1);
        sobelYBar.setBounds(320, 100, 150, 25);
        sobelYBar.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                sobelY = sobelYBar.getValue();
                sobelYLabel.setText("y=" + sobelY);
                sobelPic();
            }
        });

        JLabel freichennLabel = new JLabel("FreiChenn、Scharr、Robinson、Kirsch、Emboss");
        freichennLabel.setBounds(10, 130, 320, 25);
        
        JLabel sqrboxLabel = new JLabel("Imgproc.sqrBoxFilter(src, dst, CvType.CV_8U, new Size(alpha,alpha));");
        sqrboxLabel.setBounds(10, 160, 440, 25);

        srcMat = Imgcodecs.imread(img);
        int width = srcMat.width();
        int height = srcMat.height();

        imageView = new JLabel("");
        imageView.setBounds(40, 120, width + 50, height + 50);

        this.setTitle("图片滤镜、平滑、浮雕、边缘检测");
        this.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        this.setSize(width + 100, height + 250);
        this.getContentPane().setLayout(null);
        this.getContentPane().add(smoothLabel);
        this.getContentPane().add(smoothBar);
        this.getContentPane().add(prewittHBtn);
        this.getContentPane().add(prewittVBtn);
        this.getContentPane().add(laplacianBtn);
        this.getContentPane().add(sobelXLabel);
        this.getContentPane().add(sobelXBar);
        this.getContentPane().add(sobelYLabel);
        this.getContentPane().add(sobelYBar);
        this.getContentPane().add(freichennLabel);
        this.getContentPane().add(sqrboxLabel);
        this.getContentPane().add(imageView);

        setIcon(srcMat);
    }

    private void smoothPic() {
        Mat kernel = Mat.ones(smooth, smooth, CvType.CV_32F); // 卷积核。创建smooth*smooth像素的32位mat，通道默认1:灰度图片-单通道图像，值都是1。核有锚点一般是数组中心。
        for (int i = 0; i < kernel.rows(); i++) {
            for (int j = 0; j < kernel.cols(); j++) {
                double[] pixel = kernel.get(i, j); // 单通道，数组里只有1个元素，即值"1"。
                double b = pixel[0] / (smooth * smooth); // smooth值越大，则运算后的值越小
                pixel[0] = b;
                kernel.put(i, j, pixel);
            }
        }
        Mat dstMat = new Mat(srcMat.rows(), srcMat.cols(), srcMat.type());
        Imgproc.filter2D(srcMat, dstMat, srcMat.depth(), kernel); // 卷积运算
        // 卷积操作：
        // <1>将核的锚点放在该特定位置的像素上，同时，核内的其他值与该像素邻域的各像素重合；
        // <2>将核内各值与相应像素值相乘，并将乘积相加；
        // <3>将所得结果放到与锚点对应的像素上；
        // <4>对图像所有像素重复上述过程。
        setIcon(dstMat);
    }

    private void prewittHPic(boolean isPrewittPic) {
        if (isPrewittPic) {
            Mat kernel = new Mat(3, 3, CvType.CV_32F);
            kernel.put(0, 0, new float[]{-1, 0, 1});
            kernel.put(1, 0, new float[]{-1, 0, 1});
            kernel.put(2, 0, new float[]{-1, 0, 1});
            prewittPic(kernel);
        } else {
            setIcon(srcMat);
        }
    }

    private void prewittVPic(boolean isPrewittPic) {
        if (isPrewittPic) {
            Mat kernel = new Mat(3, 3, CvType.CV_32F);
            kernel.put(0, 0, new float[]{-1, -1, -1});
            kernel.put(1, 0, new float[]{0, 0, 0});
            kernel.put(2, 0, new float[]{1, 1, 1});
            prewittPic(kernel);
        } else {
            setIcon(srcMat);
        }
    }

    private void prewittPic(Mat kernel) {
        Mat dstMat = new Mat(srcMat.rows(), srcMat.cols(), srcMat.type());
        Imgproc.filter2D(srcMat, dstMat, srcMat.depth(), kernel); // 卷积运算
        setIcon(dstMat);
    }

    private void laplacianPic(boolean isLaplacian) {
        if (isLaplacian) {
            Mat dstMat = new Mat(srcMat.rows(), srcMat.cols(), srcMat.type());
            Imgproc.Laplacian(srcMat, dstMat, srcMat.depth()); // Laplacian(Mat src, Mat& dst, int ddepth, int ksize = 1, double scale = 1, double delta = 0, int borderType = BORDER_DEFAULT)
            // Imgproc.Laplacian(Mat src, Mat dst, int ddepth, int ksize); // ksize为奇数不可大于31。
            // Imgproc.Laplacian(Mat src, Mat dst, int ddepth, int ksize, double scale); // scale影响轮廓明显程度
            // Imgproc.Laplacian(Mat src, Mat dst, int ddepth, int ksize, double scale, double delta); // delta影响亮度
            // Imgproc.Laplacian(Mat src, Mat dst, int ddepth, int ksize, double scale, double delta, int borderType); // borderType取值：0、1、2。
            setIcon(dstMat);
        } else {
            setIcon(srcMat);
        }
    }

    private void sobelPic( ) {
        if (0 == sobelX && 0 == sobelY){
            sobelX = 1;
        }
        
        // x或y大于2，error: (-215:Assertion failed) ksize > order in function 'getSobelKernels'

        Mat dstMat = new Mat(srcMat.rows(), srcMat.cols(), srcMat.type());
        Imgproc.Sobel(srcMat, dstMat, srcMat.depth(), sobelX, sobelY); // Sobel(Mat src, Mat& dst, int ddepth, int dx, int dy, int ksize = 3, double scale = 1, double delta = 0, int borderType = BORDER_DEFAULT)
        // Imgproc.Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize); // ksize为奇数。
        // Imgproc.Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize, double scale);
        // Imgproc.Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize, double scale, double delta);
        // Imgproc.Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize, double scale, double delta, int borderType);
        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));
    }
}

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

import java.awt.image.BufferedImage;

import javax.swing.ImageIcon;

import javax.swing.JCheckBox;

import javax.swing.JFrame;

import javax.swing.JLabel;

import javax.swing.JSlider;

import javax.swing.event.ChangeEvent;

import javax.swing.event.ChangeListener;

import org.opencv.core.Core;

import org.opencv.core.CvType;

import org.opencv.core.Mat;

import org.opencv.imgcodecs.Imgcodecs;

import org.opencv.imgproc.Imgproc;

/**

* 图片滤镜、平滑、浮雕、边缘检测

public class Filter extends JFrame {

private JLabel imageView;

private int smooth = 1;

private int sobelX = 1;

private int sobelY = 1;

private Mat srcMat;

public Filter(String img) {

JLabel smoothLabel = new JLabel("平滑:" + smooth);

smoothLabel.setBounds(15, 10, 50, 25);

JSlider smoothBar = new JSlider(1, 10);

smoothBar.setValue(smooth);

smoothBar.setBounds(65, 10, 150, 25);

smoothBar.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

smooth = smoothBar.getValue();

smoothLabel.setText("平滑:" + smooth);

smoothPic();

}

});

JCheckBox prewittHBtn = new JCheckBox("水平浮雕");

prewittHBtn.setBounds(10, 40, 90, 25);

prewittHBtn.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

prewittHPic(prewittHBtn.isSelected());

}

});

JCheckBox prewittVBtn = new JCheckBox("垂直浮雕");

prewittVBtn.setBounds(130, 40, 90, 25);

prewittVBtn.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

prewittVPic(prewittVBtn.isSelected());

}

});

JCheckBox laplacianBtn = new JCheckBox("拉普拉斯边缘检测");

laplacianBtn.setBounds(10, 70, 160, 25);

laplacianBtn.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

laplacianPic(laplacianBtn.isSelected());

}

});

JLabel sobelXLabel = new JLabel("索贝尔边缘检测： x=" + sobelX);

sobelXLabel.setBounds(10, 100, 140, 25);

JSlider sobelXBar = new JSlider(1, 2);

sobelXBar.setValue(1);

sobelXBar.setBounds(140, 100, 150, 25);

sobelXBar.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

sobelX = sobelXBar.getValue();

sobelXLabel.setText("索贝尔边缘检测： x=" + sobelX);

sobelPic();

}

});

JLabel sobelYLabel = new JLabel("y=" + sobelY);

sobelYLabel.setBounds(300, 100, 40, 25);

JSlider sobelYBar = new JSlider(1, 2);

sobelYBar.setValue(1);

sobelYBar.setBounds(320, 100, 150, 25);

sobelYBar.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

sobelY = sobelYBar.getValue();

sobelYLabel.setText("y=" + sobelY);

sobelPic();

}

});

JLabel freichennLabel = new JLabel("FreiChenn、Scharr、Robinson、Kirsch、Emboss");

freichennLabel.setBounds(10, 130, 320, 25);

JLabel sqrboxLabel = new JLabel("Imgproc.sqrBoxFilter(src, dst, CvType.CV_8U, new Size(alpha,alpha));");

sqrboxLabel.setBounds(10, 160, 440, 25);

srcMat = Imgcodecs.imread(img);

int width = srcMat.width();

int height = srcMat.height();

imageView = new JLabel("");

imageView.setBounds(40, 120, width + 50, height + 50);

this.setTitle("图片滤镜、平滑、浮雕、边缘检测");

this.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);

this.setSize(width + 100, height + 250);

this.getContentPane().setLayout(null);

this.getContentPane().add(smoothLabel);

this.getContentPane().add(smoothBar);

this.getContentPane().add(prewittHBtn);

this.getContentPane().add(prewittVBtn);

this.getContentPane().add(laplacianBtn);

this.getContentPane().add(sobelXLabel);

this.getContentPane().add(sobelXBar);

this.getContentPane().add(sobelYLabel);

this.getContentPane().add(sobelYBar);

this.getContentPane().add(freichennLabel);

this.getContentPane().add(sqrboxLabel);

this.getContentPane().add(imageView);

setIcon(srcMat);

}

private void smoothPic() {

Mat kernel = Mat.ones(smooth, smooth, CvType.CV_32F); // 卷积核。创建smooth*smooth像素的32位mat，通道默认1:灰度图片-单通道图像，值都是1。核有锚点一般是数组中心。

for (int i = 0; i < kernel.rows(); i++) {

for (int j = 0; j < kernel.cols(); j++) {

double[] pixel = kernel.get(i, j); // 单通道，数组里只有1个元素，即值"1"。

double b = pixel[0] / (smooth * smooth); // smooth值越大，则运算后的值越小

pixel[0] = b;

kernel.put(i, j, pixel);

}

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

Imgproc.filter2D(srcMat, dstMat, srcMat.depth(), kernel); // 卷积运算

// 卷积操作：

// <1>将核的锚点放在该特定位置的像素上，同时，核内的其他值与该像素邻域的各像素重合；

// <2>将核内各值与相应像素值相乘，并将乘积相加；

// <3>将所得结果放到与锚点对应的像素上；

// <4>对图像所有像素重复上述过程。

setIcon(dstMat);

}

private void prewittHPic(boolean isPrewittPic) {

if (isPrewittPic) {

Mat kernel = new Mat(3, 3, CvType.CV_32F);

kernel.put(0, 0, new float[]{-1, 0, 1});

kernel.put(1, 0, new float[]{-1, 0, 1});

kernel.put(2, 0, new float[]{-1, 0, 1});

prewittPic(kernel);

} else {

setIcon(srcMat);

}

private void prewittVPic(boolean isPrewittPic) {

if (isPrewittPic) {

Mat kernel = new Mat(3, 3, CvType.CV_32F);

kernel.put(0, 0, new float[]{-1, -1, -1});

kernel.put(1, 0, new float[]{0, 0, 0});

kernel.put(2, 0, new float[]{1, 1, 1});

prewittPic(kernel);

} else {

setIcon(srcMat);

}

private void prewittPic(Mat kernel) {

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

Imgproc.filter2D(srcMat, dstMat, srcMat.depth(), kernel); // 卷积运算

setIcon(dstMat);

}

private void laplacianPic(boolean isLaplacian) {

if (isLaplacian) {

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

Imgproc.Laplacian(srcMat, dstMat, srcMat.depth()); // Laplacian(Mat src, Mat& dst, int ddepth, int ksize = 1, double scale = 1, double delta = 0, int borderType = BORDER_DEFAULT)

// Imgproc.Laplacian(Mat src, Mat dst, int ddepth, int ksize); // ksize为奇数不可大于31。

// Imgproc.Laplacian(Mat src, Mat dst, int ddepth, int ksize, double scale); // scale影响轮廓明显程度

// Imgproc.Laplacian(Mat src, Mat dst, int ddepth, int ksize, double scale, double delta); // delta影响亮度

// Imgproc.Laplacian(Mat src, Mat dst, int ddepth, int ksize, double scale, double delta, int borderType); // borderType取值：0、1、2。

setIcon(dstMat);

} else {

setIcon(srcMat);

}

private void sobelPic( ) {

if (0 == sobelX && 0 == sobelY){

sobelX = 1;

}

// x或y大于2，error: (-215:Assertion failed) ksize > order in function 'getSobelKernels'

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

Imgproc.Sobel(srcMat, dstMat, srcMat.depth(), sobelX, sobelY); // Sobel(Mat src, Mat& dst, int ddepth, int dx, int dy, int ksize = 3, double scale = 1, double delta = 0, int borderType = BORDER_DEFAULT)

// Imgproc.Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize); // ksize为奇数。

// Imgproc.Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize, double scale);

// Imgproc.Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize, double scale, double delta);

// Imgproc.Sobel(Mat src, Mat dst, int ddepth, int dx, int dy, int ksize, double scale, double delta, int borderType);

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));

}

- end

声明

本文由 cuiweiyou 原创，转载请注明出处：http://www.gaohaiyan.com/3296.html

承接App定制、企业web站点、办公系统软件设计开发，外包项目，毕设

opencv

OpenCV和Java，使用xuggle录屏
OpenCV和Java，Macos中编译OpenCV3.4.16的jar
OpenCV和Java，二值化、锐化
OpenCV和Java，模糊、油画