实现平台：windows下的Android studio1.4
依赖库：openCV3.1.0
程序安装平台：Android6.0
实现的功能：从手机中选择一张图片，检测图片的基本特征，通过menu菜单选择要检测的特征，包括Canny边缘检测、Harris角点检测、霍夫直线检测
说明：对于检测图像的基本特征的算法就不加以详细说明了，网上的资料很多，现在这里主要介绍算法以及代码的编写
1.在Androidmanifest.xml文件中添加如下代码：
<?xml version="1.0" encoding="utf-8"?>
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
package="com.example.wangshuailpp.myapplication" >
<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE"/>
<application
android:allowBackup="true"
android:icon="@mipmap/ic_launcher"
android:label="@string/app_name"
android:supportsRtl="true"
android:theme="@style/AppTheme" >
<activity
android:name=".MainActivity"
android:label="@string/app_name" >
<intent-filter>
<action android:name="android.intent.action.MAIN" />
<category android:name="android.intent.category.LAUNCHER" />
</intent-filter>
</activity>
</application>
</manifest>这里最重要的是，表示要开启手机内存的读取权限：
<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE"/>2.在布局文件中activity_main.xml文件中添加一个图片控件：
<?xml version="1.0" encoding="utf-8"?>
<RelativeLayout 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:paddingLeft="@dimen/activity_horizontal_margin"
android:paddingRight="@dimen/activity_horizontal_margin"
android:paddingTop="@dimen/activity_vertical_margin"
android:paddingBottom="@dimen/activity_vertical_margin" tools:context=".MainActivity">
<ImageView
android:id="@+id/Picture"
android:layout_height="fill_parent"
android:layout_width="fill_parent"
android:visibility="visible"
/>
</RelativeLayout>3.菜单menu_main.xml文件中添加成员：
<menu xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools" tools:context=".MainActivity">
<item
android:id="@+id/Canny"
android:title="Canny"
android:showAsAction="never"
/>
<item
android:id="@+id/Harris"
android:title="Harris"
android:showAsAction="never"
/>
<item
android:id="@+id/Hough"
android:title="Hough"
android:showAsAction="never"
/>
</menu>
4.在MainActivity.java主类中的代码：
package com.example.wangshuailpp.myapplication;
/*
功能介绍：深入OpenCV Android应用开发第二章代码，检测图像的基本特征
包括了Canny边缘检测法Sobel边缘检测法等
实现步骤：1.从手机中取出一张图片作为原始图片,通过点击menu对应的按钮开始选择图片
2.通过menu按钮选择要对照片进行的图像处理
*/
import android.content.Intent;
import android.graphics.Bitmap;
import android.graphics.BitmapFactory;
import android.net.Uri;
import android.os.Bundle;
import android.support.v7.app.ActionBarActivity;
import android.util.Log;
import android.view.Menu;
import android.view.MenuItem;
import android.widget.ImageView;
import android.widget.Toast;
import org.opencv.android.BaseLoaderCallback;
import org.opencv.android.LoaderCallbackInterface;
import org.opencv.android.OpenCVLoader;
import org.opencv.android.Utils;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.imgproc.Imgproc;
import java.io.FileNotFoundException;
import java.io.InputStream;
import java.util.Random;
public class MainActivity extends ActionBarActivity {
private final static int CANNY = 0;
private final static int HARRIS = 1;
private final static int HOUGH = 2;
private final static String TAG = "infor";
private Mat src = null;//定义一个Mat型类用于临时存放选择的图片
private Mat image = null;//用于存放得到的图片
private Mat des = null;//用于临时存放Mat型类的图片
private Bitmap resultBitmap;
private ImageView pictureView = null;//定义一个ImageView类视图用于存放选择的图片
private BaseLoaderCallback mOpenCVCallBack = new BaseLoaderCallback(this) {
@Override
public void onManagerConnected(int status) {
switch (status){
case LoaderCallbackInterface.SUCCESS:
/*在这里执行自己的语句*/
break;
default:
super.onManagerConnected(status);
break;
}
}
};
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
pictureView = (ImageView)findViewById(R.id.Picture);
}
/*启动openCV*/
@Override
protected void onResume() {
super.onResume();
OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_3_1_0, this, mOpenCVCallBack);
}
@Override
public boolean onCreateOptionsMenu(Menu menu) {
// Inflate the menu; this adds items to the action bar if it is present.
getMenuInflater().inflate(R.menu.menu_main, menu);
return true;
}
/*在这里选取要进行的操作*/
@Override
public boolean onOptionsItemSelected(MenuItem item) {
// Handle action bar item clicks here. The action bar will
// automatically handle clicks on the Home/Up button, so long
// as you specify a parent activity in AndroidManifest.xml.
int id = item.getItemId();
//对应Canny边缘检测的按钮
if (id == R.id.Canny) {
/*下面对通过Intent对象得到选择图片的Activity，最后返回图片的信息，得到图片*/
Intent pictureSelectIntent = new Intent(Intent.ACTION_PICK);//设置Action
pictureSelectIntent.setType("image/");//设置数据的类型
startActivityForResult(pictureSelectIntent,CANNY);
return true;
}
//对应Harris边缘检测的按钮
if (R.id.Harris == id){
Intent pictureSelectIntent = new Intent(Intent.ACTION_PICK);
pictureSelectIntent.setType("image/");
startActivityForResult(pictureSelectIntent,HARRIS);
return true;
}
//对应Hough的直线检测按钮
if(R.id.Hough == id){
Intent pictureSelectIntent = new Intent(Intent.ACTION_PICK);
pictureSelectIntent.setType("image/");
startActivityForResult(pictureSelectIntent,HOUGH);
return true;
}
return super.onOptionsItemSelected(item);
}
/*调用StartActivityForResult后的回调函数
* 在这个函数里面得到图片然后进行相应的处理
* */
@Override
protected void onActivityResult(int requestCode, int resultCode, Intent data) {
super.onActivityResult(requestCode, resultCode, data);
if(RESULT_OK == resultCode){
switch(requestCode){
case CANNY:
try {
Log.i(TAG,"onActivityResult00000000000");
image = GetPicture(data);
Toast.makeText(MainActivity.this, "图片选取成功", Toast.LENGTH_SHORT).show();
Log.i(TAG,"onActivityResult11111111111");
resultBitmap = MyCanny(image);
Log.i(TAG,"onActivityResult22222222222222");
pictureView.setImageBitmap(resultBitmap);
} catch (FileNotFoundException e) {
e.printStackTrace();
}
break;
case HARRIS:
try {
image = GetPicture(data);//得到图片
Toast.makeText(MainActivity.this, "图片选取成功", Toast.LENGTH_SHORT).show();
Log.i(TAG,"onActivityResult11111111111");
resultBitmap = MyHarris(image);//角点检测的图像处理
Log.i(TAG,"onActivityResult22222222222222");
pictureView.setImageBitmap(resultBitmap);
} catch (FileNotFoundException e) {
e.printStackTrace();
}
case HOUGH:
try {
image = GetPicture(data);//得到图片
Toast.makeText(MainActivity.this, "图片选取成功", Toast.LENGTH_SHORT).show();
Log.i(TAG,"onActivityResult11111111111");
resultBitmap = MyHoughLine(image);
pictureView.setImageBitmap(resultBitmap);
}catch (FileNotFoundException e) {
e.printStackTrace();
}
}
}
}
/*得到图片*/
public Mat GetPicture(Intent data) throws FileNotFoundException {
/*下面的代码是获得手机内的图片*/
final Uri imageUri = data.getData();//得到图片的路径
final InputStream imageStream = getContentResolver().openInputStream(imageUri);//得到基于路径的流文件
final Bitmap selectImage = BitmapFactory.decodeStream(imageStream);//得到了图片的位图
/*下面将位图转换成Mat型，可以进行图片的处理*/
src = new Mat(selectImage.getHeight(),selectImage.getWidth(), CvType.CV_8UC4);
Utils.bitmapToMat(selectImage,src);
return src;
}
/*下面进行图片的处理
*
* */
/*Canny边缘处理*/
public Bitmap MyCanny(Mat src){
Bitmap result;
Mat grayMat = new Mat();
Mat cannyEdges = new Mat();
Log.i(TAG,"MyCanny0000000000");
/*将图片转换成灰度图*/
Imgproc.cvtColor(src, grayMat, Imgproc.COLOR_BGR2GRAY);
Log.i(TAG, "MyCanny1111111111111111");
/*得到边缘图,这里最后两个参数控制着选择边缘的阀值上限和下限*/
Imgproc.Canny(grayMat,cannyEdges,50,300);
Log.i(TAG, "MyCanny222222222222222222222222");
/*将Mat图转换成位图*/
result = Bitmap.createBitmap(src.cols(),src.rows(),Bitmap.Config.ARGB_8888);
Utils.matToBitmap(cannyEdges,result);
Log.i(TAG, "MyCanny3333333333333333333333");
return result;
}
/*Harris角点检测*/
public Bitmap MyHarris(Mat src){
Bitmap resultHarris;
Mat grayMat = new Mat();
Mat corners = new Mat();
Log.i(TAG,"MyHarris00000000000000000000");
/*将图片转换成灰度图*/
Imgproc.cvtColor(src,grayMat,Imgproc.COLOR_BGR2GRAY);
Log.i(TAG, "MyHarris1111111111111111111");
/*找出角点*/
Mat tempDst = new Mat();
Imgproc.cornerHarris(grayMat,tempDst,2,3,0.04);
Log.i(TAG, "MyHarris2222222222222222222");
/*归一化Harris角点的输出*/
Mat tempDstNorm = new Mat();
Core.normalize(tempDst,tempDstNorm,0,255,Core.NORM_MINMAX);
Core.convertScaleAbs(tempDstNorm, corners);
Log.i(TAG, "MyHarris33333333333333333333");
/*在新的图片上绘制角点*/
Random r = new Random();
for(int i = 0; i < tempDstNorm.cols(); i++){
for (int j = 0;j <tempDstNorm.rows(); j++){
double[] value = tempDstNorm.get(j,i);
if(value[0] > 250){//决定了画出哪些角点，值越大选择画出的点就越少。如果程序跑的比较慢，就是由于值选取的太小，导致画的点过多
Imgproc.circle(corners, new Point(i,j),5,new Scalar(r.nextInt(255)),2);
}
}
}
Log.i(TAG,"MyHarris4444444444444444444444444");
/*将Mat图转换成位图*/
resultHarris = Bitmap.createBitmap(src.cols(),src.rows(),Bitmap.Config.ARGB_8888);//这一步至关重要，必须初始化Bitmap对象的大小
Utils.matToBitmap(corners, resultHarris);
return resultHarris;
}
/*Hough直线检测*/
public Bitmap MyHoughLine(Mat src){
Bitmap resultHough;
Mat grayMat = new Mat();
Mat cannyEdges = new Mat();
Mat lines = new Mat();
Mat origination = new Mat(src.size(),CvType.CV_8UC1);
src.copyTo(origination);//拷贝
/*通过Canny得到边缘图*/
Imgproc.cvtColor(origination,grayMat,Imgproc.COLOR_BGR2GRAY);
Imgproc.Canny(grayMat,cannyEdges,50,300);
//Mat cannyEdges = new Mat(resultHough.getHeight(),resultHough.getWidth(),CvType.CV_8UC1);
Log.i(TAG,"MyHoughLine00000000000000");
/*获得直线图*/
Imgproc.HoughLinesP(cannyEdges,lines,1,Math.PI/180,10,0,50);
Log.i(TAG, "MyHoughLine111111111111111");
Mat houghLines = new Mat();
houghLines.create(cannyEdges.rows(),cannyEdges.cols(),CvType.CV_8UC1);
Log.i(TAG, "MyHoughLine2222222222222222222");
/*在图线的上绘制直线*/
for(int i = 0;i < lines.rows();i++){
double[] points = lines.get(i,0);
if(null != points){
double x1,y1,x2,y2;
x1 = points[0];
y1 = points[1];
x2 = points[2];
y2 = points[3];
Point pt1 = new Point(x1,y1);
Point pt2 = new Point(x2,y2);
/*在一幅图像上绘制直线*/
Imgproc.line(houghLines,pt1,pt2,new Scalar(55,100,195),3);
}
}
Log.i(TAG, "MyHoughLine3333333333333333333333333");
resultHough = Bitmap.createBitmap(src.cols(),src.rows(),Bitmap.Config.ARGB_8888);
Utils.matToBitmap(houghLines,resultHough);
Log.i(TAG, "MyHoughLine44444444444444444444444444444");
return resultHough;
}
}
这里需要注意的事项：
1.在霍夫直线检测中有一句代码，很多网上的程序都不对，都写成了
double[] points = lines.get(0,i); 其实是
double[] points = lines.get(i,0);
写成第一种，会导致只会画出一条直线。
其他的都可以在程序的解释中看到，在这里就不都说了，下面直接贴结果，分别是原图，Canny，Harri，霍夫直线。
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