OpenCV.自定义卷积核.梯度

自定义卷积核—梯度

OpenCV除了提供由库进行计算的kernel，还支持自定义kernel来进行自定义滤波。常见的包括模糊、锐化、梯度计算等方式。利用梯度可检测图片边缘变化较大的地方，在二值化和特征提取时有很大作用。自定义kernel的实现依赖于filter2D() 函数。下面是该函数的声明：

filter2D(src, dst, ddepth, kernel);

各参数解释如下：

• src
  表示此操作的源(输入图像)的Mat对象。

• dst
  表示此操作的目标(输出图像)的Mat对象。

• ddepth
  输出图像深度，值为-1则表示与输入图像一致。

• kernel
  自定义的卷积核。

Java代码（JavaFX Controller层）

public class Controller{
    
    

    @FXML private Text fxText;
    @FXML private ImageView imageView;

    @FXML public void handleButtonEvent(ActionEvent actionEvent) throws IOException {
    
    

        Node source = (Node) actionEvent.getSource();
        Window theStage = source.getScene().getWindow();
        FileChooser fileChooser = new FileChooser();
        FileChooser.ExtensionFilter extFilter = new FileChooser.ExtensionFilter("PNG files (*.png)", "*.png");
        fileChooser.getExtensionFilters().add(extFilter);
        fileChooser.getExtensionFilters().add(new FileChooser.ExtensionFilter("JPG Files(*.jpg)", "*.jpg"));
        File file = fileChooser.showOpenDialog(theStage);

        runInSubThread(file.getPath());

    }

    private void runInSubThread(String filePath){
    
    
        new Thread(new Runnable() {
    
    
            @Override
            public void run() {
    
    
                try {
    
    
                    WritableImage writableImage = filter2DOfGradient(filePath);

                    Platform.runLater(new Runnable() {
    
    
                        @Override
                        public void run() {
    
    
                            imageView.setImage(writableImage);
                        }
                    });

                } catch (IOException e) {
    
    
                    e.printStackTrace();
                }
            }
        }).start();
    }

    private WritableImage filter2DOfGradient(String filePath) throws IOException {
    
    
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

        Mat src = Imgcodecs.imread(filePath);
        Mat dst = new Mat();

        // Self define kernel of gradient.
        Mat k_x = new Mat(3,3,CvType.CV_32FC1);
        Mat k_y = new Mat(3,3,CvType.CV_32FC1);
        // Kernel of X direction gradient.
        float[] robert_x = new float[]{
    
    -1, 0,
                                       0,1};
        k_x.put(0, 0, robert_x);
        // Kernel of Y direction gradient.
        float[] robert_y = new float[]{
    
    0, 1,
                                       -1,0};
        k_y.put(0, 0, robert_y);

        Imgproc.filter2D(src, dst, -1, k_x);
        Imgproc.filter2D(src, dst, -1, k_y);

        MatOfByte matOfByte = new MatOfByte();
        Imgcodecs.imencode(".jpg", dst, matOfByte);

        byte[] bytes = matOfByte.toArray();
        InputStream in = new ByteArrayInputStream(bytes);
        BufferedImage bufImage = ImageIO.read(in);

        WritableImage writableImage = SwingFXUtils.toFXImage(bufImage, null);

        return writableImage;
    }

}

运行图