[人工智能]OpenCV.自适应阈值.TRIANGLE

自适应阈值.TRIANGLE

对于阈值操作，不仅可以手动设置阈值，还可以自动计算阈值，即根据输入源本身特征进行自适应阈值。本节自适应为TRIANGLE。TRIANGLE的含义为将灰度输入源的直方图寻找其最大峰值，从最大峰值作为新三角形的顶点作到水平轴的45°连线，在这个构成的三角形作到直方图的距离d，d即为阈值T。在OpenCV中，其枚举为Imgproc.THRESH_TRIANGLE。

其几何描述如下：

Java代码（JavaFX Controller层）

public class Controller{

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

    @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 = thresholdOfTriangle(filePath);

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

                } catch (IOException e) {
                    e.printStackTrace();
                }
            }
        }).start();
    }
    
    private WritableImage thresholdOfTriangle(String filePath) throws IOException {
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

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

        // Construct an empty mat instance to change src into gray image.
        Mat gray = new Mat();
        Imgproc.cvtColor(src, gray, Imgproc.COLOR_BGR2GRAY);
        Imgproc.threshold(gray, dst, 0, 255, Imgproc.THRESH_BINARY | Imgproc.THRESH_TRIANGLE);

        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