Android OpenCV 边缘检测 Canny 的使用

先看下实现的效果图

下面看下代码使用

Canny(Mat image, Mat edges, double threshold1, double threshold2, int apertureSize, boolean L2gradient)

 @param image 8-bit input image.
* @param edges output edge map; single channels 8-bit image, which has the same size as image .
* @param threshold1 first threshold for the hysteresis procedure.
* @param threshold2 second threshold for the hysteresis procedure.
* @param apertureSize aperture size for the Sobel operator.
* @param L2gradient a flag, indicating whether a more accurate \(L_2\) norm
* \(=\sqrt{(dI/dx)^2 + (dI/dy)^2}\) should be used to calculate the image gradient magnitude (
* L2gradient=true ), or whether the default \(L_1\) norm \(=|dI/dx|+|dI/dy|\) is enough (
* L2gradient=false )
第​​​​​​​一个参数image：输入图像，单通道8位图像
第二个参数edges：输出边缘图像，需要和原图像有一样尺寸和类型
第三个参数threshold1：第一个滞后性阈值
第四个参数threshold2：第二个滞后性阈值 这个数值越大轮廓越少，
第五个参数apertureSize：表示应用sobel算子的孔径大小其有默认值3
第六个参数L2gradient：bool类型的L2gradient，一个计算图像梯度幅值的标识阈值1和阈值2中较小的用于边缘的连接，较大的用于控制强边缘的初始段。高低阈值比在2:1和3:1之间时最佳的

 

public class CanneyActivity extends AppCompatActivity {

    private ImageView imageView;
    private Bitmap bitmap;
    @Override
    protected void onCreate(@Nullable Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.canney_activity_layout);

        imageView = findViewById(R.id.img);

        bitmap = ((BitmapDrawable) getResources().getDrawable(R.mipmap.photo)).getBitmap();
        imageView.setImageBitmap(bitmap);

        findViewById(R.id.btn).setOnClickListener(new View.OnClickListener() {
            @Override
            public void onClick(View v) {
                Bitmap canneyBitmap = toCanneyByOpencv(bitmap);
                imageView.setImageBitmap(canneyBitmap);

            }
        });
    }

    private Bitmap toCanneyByOpencv(Bitmap bitmap) {
        Mat mat = new Mat();
        Utils.bitmapToMat(bitmap, mat);
        Mat gray= new Mat();
        // 转灰度图片
//        Imgproc.cvtColor(mat, gray, Imgproc.COLOR_BGR2GRAY);
        // 使用3x3的内核来降噪
//        Imgproc.blur(mat, gray, new Size(3,3));
        // 高斯降噪
//        Imgproc.GaussianBlur(mat, gray, new Size(3,3),5,5);
        //3 描绘边缘
        Imgproc.Canny(mat, gray, 50, 200, 3, false);
        Utils.matToBitmap(gray, bitmap);
        return bitmap;

    }

    @Override
    protected void onResume() {
        super.onResume();
        OpenCVLoader.initDebug();
    }


}

xml 代码

<?xml version="1.0" encoding="utf-8"?>
<LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
        xmlns:tools="http://schemas.android.com/tools"
        android:layout_width="match_parent"
        android:layout_height="match_parent"
        android:orientation="vertical"
        tools:context=".MainActivity">

    <ImageView
            android:id="@+id/img"
            android:layout_width="wrap_content"
            android:layout_height="wrap_content"
            android:scaleType="fitXY" />

    <Button
            android:id="@+id/btn"
            android:layout_width="wrap_content"
            android:layout_height="wrap_content"
            android:text="边缘检测"/>



</LinearLayout>

可以修改threshold2 查看轮廓

public class CanneyActivity extends AppCompatActivity {

    private ImageView imageView;
    private Bitmap bitmap;
    @Override
    protected void onCreate(@Nullable Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.canney_activity_layout);

        imageView = findViewById(R.id.img);

        bitmap = ((BitmapDrawable) getResources().getDrawable(R.mipmap.photo)).getBitmap();
        imageView.setImageBitmap(bitmap);

        findViewById(R.id.btn).setOnClickListener(new View.OnClickListener() {
            @Override
            public void onClick(View v) {
                Bitmap canneyBitmap = toCanneyByOpencv(bitmap);
                imageView.setImageBitmap(canneyBitmap);

            }
        });
    }

    private Bitmap toCanneyByOpencv(Bitmap bitmap) {
        Mat mat = new Mat();
        Utils.bitmapToMat(bitmap, mat);
        Mat gray= new Mat();
        // 转灰度图片
//        Imgproc.cvtColor(mat, gray, Imgproc.COLOR_BGR2GRAY);
        // 使用3x3的内核来降噪
//        Imgproc.blur(mat, gray, new Size(3,3));
        // 高斯降噪
//        Imgproc.GaussianBlur(mat, gray, new Size(3,3),5,5);
        //3 描绘边缘
        Imgproc.Canny(mat, gray, 3, 3, 3, false);
        Utils.matToBitmap(gray, bitmap);
        return bitmap;

    }

    @Override
    protected void onResume() {
        super.onResume();
        OpenCVLoader.initDebug();
    }

}

这个时候在看下效果图如下