android openCV检测图像的基本特征，包括Canny边缘检测、Harris角点检测、霍夫直线检测-基于Android studio

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。