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在移动应用开发中,图像处理是一个非常重要的领域。随着智能手机摄像头性能的不断提升,开发者可以利用手机摄像头进行各种复杂的图像处理任务。OpenCV(Open Source Computer Vision Library)是一个开源的计算机视觉库,提供了丰富的图像处理功能。本文将详细介绍如何在Android平台上使用OpenCV4Android库,通过手机摄像头获取Canny边缘。
OpenCV4Android是OpenCV库的Android版本,专门为Android平台优化。它提供了Java和C++接口,开发者可以根据需求选择合适的接口进行开发。OpenCV4Android支持多种图像处理算法,包括边缘检测、特征提取、目标跟踪等。
首先,确保你已经安装了Android Studio。Android Studio是Google官方推荐的Android应用开发工具,提供了强大的代码编辑、调试和性能分析功能。
opencv-android-sdk
文件夹。Start a new Android Studio project
。Empty Activity
模板,点击Next
。OpenCVCannyEdgeDetection
,选择保存路径,点击Finish
。File
-> New
-> Import Module
。opencv-android-sdk/sdk/java
路径,点击Finish
。build.gradle
文件中添加OpenCV库的依赖:
dependencies {
implementation project(':opencv')
}
在AndroidManifest.xml文件中添加摄像头权限:
<uses-permission android:name="android.permission.CAMERA" />
MainActivity.java
中,添加摄像头初始化代码:
“`java
import android.Manifest;
import android.content.pm.PackageManager;
import android.hardware.Camera;
import android.os.Bundle;
import android.support.v4.app.ActivityCompat;
import android.support.v4.content.ContextCompat;
import android.support.v7.app.AppCompatActivity;
import android.view.SurfaceView;
import android.widget.FrameLayout;public class MainActivity extends AppCompatActivity { private Camera mCamera; private SurfaceView mPreview; private FrameLayout mFrameLayout;
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
mFrameLayout = findViewById(R.id.camera_preview);
if (ContextCompat.checkSelfPermission(this, Manifest.permission.CAMERA)
!= PackageManager.PERMISSION_GRANTED) {
ActivityCompat.requestPermissions(this, new String[]{Manifest.permission.CAMERA}, 1);
} else {
initializeCamera();
}
}
private void initializeCamera() {
mCamera = Camera.open();
mPreview = new CameraPreview(this, mCamera);
mFrameLayout.addView(mPreview);
}
}
2. 创建`CameraPreview`类,用于显示摄像头预览:
```java
import android.content.Context;
import android.hardware.Camera;
import android.view.SurfaceHolder;
import android.view.SurfaceView;
public class CameraPreview extends SurfaceView implements SurfaceHolder.Callback {
private SurfaceHolder mHolder;
private Camera mCamera;
public CameraPreview(Context context, Camera camera) {
super(context);
mCamera = camera;
mHolder = getHolder();
mHolder.addCallback(this);
mHolder.setType(SurfaceHolder.SURFACE_TYPE_PUSH_BUFFERS);
}
@Override
public void surfaceCreated(SurfaceHolder holder) {
try {
mCamera.setPreviewDisplay(holder);
mCamera.startPreview();
} catch (Exception e) {
e.printStackTrace();
}
}
@Override
public void surfaceChanged(SurfaceHolder holder, int format, int width, int height) {
if (mHolder.getSurface() == null) {
return;
}
try {
mCamera.stopPreview();
} catch (Exception e) {
e.printStackTrace();
}
try {
mCamera.setPreviewDisplay(mHolder);
mCamera.startPreview();
} catch (Exception e) {
e.printStackTrace();
}
}
@Override
public void surfaceDestroyed(SurfaceHolder holder) {
// Release the camera preview
}
}
MainActivity.java
中,添加图像捕获代码:
“`java
import android.graphics.Bitmap;
import android.graphics.BitmapFactory;
import android.hardware.Camera;
import android.os.Environment;
import android.util.Log;
import android.widget.ImageView;public class MainActivity extends AppCompatActivity { private Camera mCamera; private SurfaceView mPreview; private FrameLayout mFrameLayout; private ImageView mImageView;
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
mFrameLayout = findViewById(R.id.camera_preview);
mImageView = findViewById(R.id.image_view);
if (ContextCompat.checkSelfPermission(this, Manifest.permission.CAMERA)
!= PackageManager.PERMISSION_GRANTED) {
ActivityCompat.requestPermissions(this, new String[]{Manifest.permission.CAMERA}, 1);
} else {
initializeCamera();
}
}
private void initializeCamera() {
mCamera = Camera.open();
mPreview = new CameraPreview(this, mCamera);
mFrameLayout.addView(mPreview);
mCamera.setPreviewCallback(new Camera.PreviewCallback() {
@Override
public void onPreviewFrame(byte[] data, Camera camera) {
Camera.Size size = camera.getParameters().getPreviewSize();
Bitmap bitmap = BitmapFactory.decodeByteArray(data, 0, data.length);
mImageView.setImageBitmap(bitmap);
}
});
}
}
### Canny边缘检测算法
Canny边缘检测是一种多阶段的边缘检测算法,主要包括以下几个步骤:
1. 高斯滤波:去除图像噪声。
2. 计算梯度:使用Sobel算子计算图像的梯度幅值和方向。
3. 非极大值抑制:保留梯度幅值最大的像素,抑制其他像素。
4. 双阈值检测:通过高低阈值确定边缘。
### 实现Canny边缘检测
1. 在`MainActivity.java`中,添加Canny边缘检测代码:
```java
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.android.Utils;
import org.opencv.imgproc.Imgproc;
public class MainActivity extends AppCompatActivity {
private Camera mCamera;
private SurfaceView mPreview;
private FrameLayout mFrameLayout;
private ImageView mImageView;
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
mFrameLayout = findViewById(R.id.camera_preview);
mImageView = findViewById(R.id.image_view);
if (ContextCompat.checkSelfPermission(this, Manifest.permission.CAMERA)
!= PackageManager.PERMISSION_GRANTED) {
ActivityCompat.requestPermissions(this, new String[]{Manifest.permission.CAMERA}, 1);
} else {
initializeCamera();
}
}
private void initializeCamera() {
mCamera = Camera.open();
mPreview = new CameraPreview(this, mCamera);
mFrameLayout.addView(mPreview);
mCamera.setPreviewCallback(new Camera.PreviewCallback() {
@Override
public void onPreviewFrame(byte[] data, Camera camera) {
Camera.Size size = camera.getParameters().getPreviewSize();
Mat rgba = new Mat(size.height, size.width, CvType.CV_8UC4);
Mat gray = new Mat(size.height, size.width, CvType.CV_8UC1);
Mat edges = new Mat(size.height, size.width, CvType.CV_8UC1);
Utils.bitmapToMat(BitmapFactory.decodeByteArray(data, 0, data.length), rgba);
Imgproc.cvtColor(rgba, gray, Imgproc.COLOR_RGBA2GRAY);
Imgproc.Canny(gray, edges, 50, 150);
Bitmap resultBitmap = Bitmap.createBitmap(edges.cols(), edges.rows(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(edges, resultBitmap);
mImageView.setImageBitmap(resultBitmap);
}
});
}
}
为了提升性能,可以降低图像的分辨率。在Camera.Parameters
中设置预览尺寸:
Camera.Parameters parameters = mCamera.getParameters();
parameters.setPreviewSize(640, 480);
mCamera.setParameters(parameters);
为了避免UI线程阻塞,可以将图像处理任务放在后台线程中执行:
private class ImageProcessingTask extends AsyncTask<byte[], Void, Bitmap> {
@Override
protected Bitmap doInBackground(byte[]... data) {
Camera.Size size = mCamera.getParameters().getPreviewSize();
Mat rgba = new Mat(size.height, size.width, CvType.CV_8UC4);
Mat gray = new Mat(size.height, size.width, CvType.CV_8UC1);
Mat edges = new Mat(size.height, size.width, CvType.CV_8UC1);
Utils.bitmapToMat(BitmapFactory.decodeByteArray(data[0], 0, data[0].length), rgba);
Imgproc.cvtColor(rgba, gray, Imgproc.COLOR_RGBA2GRAY);
Imgproc.Canny(gray, edges, 50, 150);
Bitmap resultBitmap = Bitmap.createBitmap(edges.cols(), edges.rows(), Bitmap.Config.ARGB_8888);
Utils.matToBitmap(edges, resultBitmap);
return resultBitmap;
}
@Override
protected void onPostExecute(Bitmap resultBitmap) {
mImageView.setImageBitmap(resultBitmap);
}
}
本文详细介绍了如何在Android平台上使用OpenCV4Android库,通过手机摄像头获取Canny边缘。从环境搭建、项目创建、摄像头初始化到图像处理和Canny边缘检测的实现,涵盖了整个开发流程。通过优化图像分辨率和多线程处理,可以显著提升应用的性能。希望本文能为你在Android图像处理开发中提供有价值的参考。
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