Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现

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摘要：基于opencv4.6.0，Android平台实现了人脸识别功能。该功能通过调用OpenCV库中的相关算法和接口，实现对人脸的识别、定位和分析。该功能具有高效、准确、实时性强等特点，可广泛应用于安防监控、人脸识别验证、社交娱乐等领域。通过不断优化算法和提升技术，Android平台的人脸识别功能将会更加完善和普及。

前言

步骤：

1.整合opencv

2.获取相机的SurfaceView传到native层去检测(亦或是不断的获取SurfaceView的Bitmap，传到native层)

3.检测人脸，在本地保存人脸特征信息

4.上传至后台(不实现)

人脸识别实现的思路(例：人脸登录)

1.人脸信息录入

1.1获取相机的Bitmap，检测人脸(保证人脸信息比较精准) 人脸要足够大，当前范围内人脸只能有一张人脸，正常、眨眼睛、张嘴巴(3张人脸信息)

1.2获取到人脸必须要保存人脸特征信息，然后上传至后台(后台会再次做算法优化)，保存到数据库

2.人脸特征值匹配

2.1获取相机的Bitmap，检测人脸(保证人脸信息比较精准) 人脸要足够大，当前范围内人脸只能有一张人脸，正常、眨眼睛、张嘴巴(3张人脸信息)

2.2从后台去查询用户进行登录

一.Android Studio配置opencv

1.opencv资源获取

opencv官网：Home - OpenCV

opencv最新的版本是4.6.0于2022年06月07日发布，4.6.0网址：OpenCV 4.6.0 Is Now Available! - OpenCV

opencv 4.6.0android sdk 下载链接https://nchc.dl.sourceforge.net/project/opencvlibrary/4.6.0/opencv-4.6.0-android-sdk.zip

2.解压opencv-4.6.0-android-sdk.zip文件

解压之后的文件夹:OpenCV-android-sdk

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第1张

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第2张

samples：所有与android相关的一些示例代码，基本全部是java代码，封装了很多功能(图片转成灰度，高斯模糊，边缘检测)

sdk：所有的资源，so库，头文件，NDK自己动手写

源码下载链接：https://github.com/opencv/opencv/archive/4.6.0.zip

3.新建Android项目(native c++)

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第3张

C++ Standard 选择C++11

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第4张

在main目录下新建jni文件夹

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第5张

将OpenCV-android-sdk\sdk\native\jni下的include文件夹复制至项目中的jni文件夹下

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第6张

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第7张

将OpenCV-android-sdk\sdk\native\libs下的armeabi-v7a文件夹复制至jni文件夹下

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第8张

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第9张

3.1配置CMakeLists.txt

引入头文件

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第10张

添加opencv库并设置目标属性(注意路径)

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第11张

添加目标链接库opencv-lib

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第12张

CMakeLists.txt内容：

# For more information about using CMake with Android Studio, read the
# documentation: https://d.android.com/studio/projects/add-native-code.html
# Sets the minimum version of CMake required to build the native library.
cmake_minimum_required(VERSION 3.10.2)
# Declares and names the project.
project("opencvtestapplication")
#需要引入我们头文件，以这个配置的目录为基准
include_directories(${CMAKE_SOURCE_DIR}/../jni/include)
# Creates and names a library, sets it as either STATIC
# or SHARED, and provides the relative paths to its source code.
# You can define multiple libraries, and CMake builds them for you.
# Gradle automatically packages shared libraries with your APK.
add_library( # Sets the name of the library.
             native-lib
             # Sets the library as a shared library.
             SHARED
             # Provides a relative path to your source file(s).
             native-lib.cpp )
# 添加opencv的库
add_library(
        opencv-lib
        SHARED
        IMPORTED)
set_target_properties(
        opencv-lib
        PROPERTIES IMPORTED_LOCATION
        ${CMAKE_SOURCE_DIR}/../jni/armeabi-v7a/libopencv_java4.so)
# Searches for a specified prebuilt library and stores the path as a
# variable. Because CMake includes system libraries in the search path by
# default, you only need to specify the name of the public NDK library
# you want to add. CMake verifies that the library exists before
# completing its build.
find_library( # Sets the name of the path variable.
              log-lib
              # Specifies the name of the NDK library that
              # you want CMake to locate.
              log )
# Specifies libraries CMake should link to your target library. You
# can link multiple libraries, such as libraries you define in this
# build script, prebuilt third-party libraries, or system libraries.
target_link_libraries( # Specifies the target library.
                       native-lib opencv-lib
                       # Links the target library to the log library
                       # included in the NDK.
                       ${log-lib} )

3.2修改app下的build.gradle文件只支持armv7

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第13张

同步运行项目至手机设备

出现如下图所示错误：

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第14张

java.lang.UnsatisfiedLinkError: dlopen failed: library "libc++_shared.so" not found

解决方式如下：

修改app下的build.gradle文件

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第15张

重新同步项目并运行项目至手机设备

3.3新建FaceDetection类

FaceDetection内容如下：

package com.suoer.ndk.opencvtestapplication;
import android.graphics.Bitmap;
public class FaceDetection {
    // Used to load the 'native-lib' library on application startup.
    static {
        System.loadLibrary("native-lib");
    }
    /**
     * 检测人脸并保存人脸信息
     * @param faceBitmap
     */
    public native int faceDetectionSaveInfo(Bitmap faceBitmap);
    /**
     * 加载人脸识别的分类器文件
     * @param filePath
     */
    public native boolean loadCascade(String filePath);
}

3.4修改MainActivity类

因为需要拍照以及保存图片，所以需要权限处理。这里使用rxpermissions

rxpermissions的具体使用请参照github链接：GitHub - tbruyelle/RxPermissions: Android runtime permissions powered by RxJava2

因为保存图片是耗时操作，需要开启子线程完成，所以需要处理线程问题。这里使用rxandroid

rxandroid的具体使用请参照github链接：GitHub - ReactiveX/RxAndroid: RxJava bindings for Android

修改app下的build.gradle文件

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第16张

app下的build.gradle文件内容：

plugins {
    id 'com.android.application'
}
android {
    compileSdkVersion 32
    buildToolsVersion "32.0.0"
    defaultConfig {
        applicationId "com.suoer.ndk.opencvtestapplication"
        minSdkVersion 16
        targetSdkVersion 32
        versionCode 1
        versionName "1.0"
        testInstrumentationRunner "androidx.test.runner.AndroidJUnitRunner"
        externalNativeBuild {
            cmake {
                cppFlags "-std=c++11 -Wno-nonportable-include-path -Wno-deprecated-register -Wno-writable-strings"
                //远程下载
                arguments "-DANDROID_STL=c++_shared"
            }
        }
        ndk {
            abiFilters("armeabi-v7a")
        }
    }
    buildTypes {
        release {
            minifyEnabled false
            proguardFiles getDefaultProguardFile('proguard-android-optimize.txt'), 'proguard-rules.pro'
        }
    }
    externalNativeBuild {
        cmake {
            path "src/main/cpp/CMakeLists.txt"
            version "3.10.2"
        }
    }
    compileOptions {
        sourceCompatibility JavaVersion.VERSION_1_8
        targetCompatibility JavaVersion.VERSION_1_8
    }
}
dependencies {
    implementation 'androidx.appcompat:appcompat:1.1.0'
    implementation 'com.google.android.material:material:1.1.0'
    implementation 'androidx.constraintlayout:constraintlayout:1.1.3'
    testImplementation 'junit:junit:4.+'
    androidTestImplementation 'androidx.test.ext:junit:1.1.1'
    androidTestImplementation 'androidx.test.espresso:espresso-core:3.2.0'
    implementation 'com.github.tbruyelle:rxpermissions:0.12'
    implementation 'io.reactivex.rxjava3:rxandroid:3.0.0'
}

修改项目下的build.gradle文件

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第17张

项目下的build.gradle文件内容：

// Top-level build file where you can add configuration options common to all sub-projects/modules.
buildscript {
    repositories {
        google()
        jcenter()
    }
    dependencies {
        classpath "com.android.tools.build:gradle:4.1.0"
        // NOTE: Do not place your application dependencies here; they belong
        // in the individual module build.gradle files
    }
}
allprojects {
    repositories {
        google()
        jcenter()
        maven { url 'https://jitpack.io' }
        maven { url "https://oss.jfrog.org/libs-snapshot" }
    }
}
task clean(type: Delete) {
    delete rootProject.buildDir
}

修改AndroidManifest.xml添加权限

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第18张

MainActivity类内容如下：

package com.suoer.ndk.opencvtestapplication;
import android.Manifest;
import android.content.Context;
import android.content.pm.PackageManager;
import android.graphics.Bitmap;
import android.os.Bundle;
import android.util.Log;
import android.view.SurfaceView;
import android.view.View;
import android.view.Window;
import android.view.WindowManager;
import android.widget.Button;
import android.widget.ImageView;
import android.widget.Toast;
import com.suoer.ndk.opencvtestapplication.camerahandle.BitmapInterface;
import com.suoer.ndk.opencvtestapplication.camerahandle.CameraSurfaceHolder;
import com.suoer.ndk.opencvtestapplication.camerahandle.FrontCamera;
import com.suoer.ndk.opencvtestapplication.camerahandle.SaveImageTask;
import com.suoer.ndk.opencvtestapplication.camerahandle.SurfaceViewCallback;
import com.tbruyelle.rxpermissions3.RxPermissions;
import java.io.ByteArrayOutputStream;
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.InputStream;
import androidx.appcompat.app.AppCompatActivity;
import io.reactivex.rxjava3.functions.Consumer;
public class MainActivity extends AppCompatActivity {
    private static final String TAG = "MainActivity";
    private SurfaceView mSurfaceView;
    private ImageView faceImg;
    private Button faceDetectionBtn;
    private FaceDetection mFaceDetection;
    private File mCascadeFile;
    private CameraSurfaceHolder mCameraSurfaceHolder=new CameraSurfaceHolder();
    private SurfaceViewCallback mSurfaceViewCallback;
    private FrontCamera mFrontCamera;
    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        requestWindowFeature(Window.FEATURE_NO_TITLE);
        getWindow().addFlags(WindowManager.LayoutParams.FLAG_FULLSCREEN);
        initView();
        applyPermission();
        initFaceDetection();
    }
    private void initFaceDetection() {
        copyCascadeFile();
        mFaceDetection = new FaceDetection();
        if (mFaceDetection != null) {
            boolean load = mFaceDetection.loadCascade(mCascadeFile.getAbsolutePath());
            if (load) {
                Toast.makeText(this, "加载分类器文件成功！", Toast.LENGTH_SHORT).show();
            } else {
                Toast.makeText(this, "加载分类器文件失败！", Toast.LENGTH_SHORT).show();
            }
        }
    }
    //申请权限
    private void applyPermission() {
        if (!checkCameraHardware(this)) {
            return;
        }
        RxPermissions rxPermissions = new RxPermissions(this);
        rxPermissions.request(Manifest.permission.READ_EXTERNAL_STORAGE, Manifest.permission.WRITE_EXTERNAL_STORAGE, Manifest.permission.CAMERA).subscribe(new Consumer() {
            @Override
            public void accept(Boolean aBoolean) throws Throwable {
                if (aBoolean) {
                    Log.e(TAG, "accept: " + aBoolean);
                    faceDetectionBtn.setVisibility(View.VISIBLE);
                    mSurfaceView.setVisibility(View.VISIBLE);
                    //权限全部获取
                    initSurfaceViewPreView();
                }
            }
        });
    }
    private void initSurfaceViewPreView() {
        mCameraSurfaceHolder.setCameraSurfaceHolder(MainActivity.this, mSurfaceView);
        mSurfaceViewCallback = mCameraSurfaceHolder.mSurfaceViewCallback;
        if (mSurfaceViewCallback != null) {
            mFrontCamera = mSurfaceViewCallback.mFrontCamera;
        }
    }
    ;
    private void initView() {
        setContentView(R.layout.activity_main);
        mSurfaceView = findViewById(R.id.face_surfaceView);
        mSurfaceView.setVisibility(View.GONE);
        faceDetectionBtn = findViewById(R.id.faceDetectionBtn);
        faceImg = findViewById(R.id.faceImg);
        faceDetectionBtn.setOnClickListener(new View.OnClickListener() {
            @Override
            public void onClick(View v) {
                if (mFrontCamera != null) {
                    //拍照的时候进行人脸识别
                    mFrontCamera.takePicture(new BitmapInterface() {
                        @Override
                        public void setBitMap(Bitmap bitMap) {
                            if(bitMap==null){
                                Toast.makeText(MainActivity.this,"拍照失败！",Toast.LENGTH_SHORT).show();
                                return;
                            }
                            //人脸识别
                            int result = mFaceDetection.faceDetectionSaveInfo(bitMap);
                            if (result != 0) {
                                Toast.makeText(MainActivity.this, "检测人脸失败!", Toast.LENGTH_SHORT).show();
                                return;
                            }
                            faceImg.setVisibility(View.VISIBLE);
                            faceImg.setImageBitmap(bitMap);
                            byte[]data= bitmap2byte(bitMap);
                            //rxandroid实现开启子线程保存文件
                            new SaveImageTask(MainActivity.this,faceImg).saveImage(data);
                            //AsyncTask异步任务实现开启子线程保存文件
                            //new SaveImageAsyncTask(MainActivity.this,faceImg).execute(data);
                        }
                    });
                }
            }
        });
    }
    private byte[] bitmap2byte(Bitmap photoBitmap){
        创建对应的流对象
        ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream();
        photoBitmap.compress(Bitmap.CompressFormat.JPEG,100,byteArrayOutputStream);//将流对象与Bitmap对象进行关联。
        byte [] array=byteArrayOutputStream.toByteArray();//使用流对象，将Bitmap对象转换为byte[]数组
        return array;
    }

    private void copyCascadeFile() {
        try {
            // load cascade file from application resources
            InputStream is = getResources().openRawResource(R.raw.lbpcascade_frontalface);
            File cascadeDir = getDir("cascade", Context.MODE_PRIVATE);
            mCascadeFile = new File(cascadeDir, "lbpcascade_frontalface.xml");
            if (mCascadeFile.exists()) return;
            FileOutputStream os = new FileOutputStream(mCascadeFile);
            byte[] buffer = new byte[4096];
            int bytesRead;
            while ((bytesRead = is.read(buffer)) != -1) {
                os.write(buffer, 0, bytesRead);
            }
            is.close();
            os.close();
            cascadeDir.delete();
        } catch (IOException e) {
            e.printStackTrace();
            Log.e(TAG, "Failed to load cascade. Exception thrown: " + e);
        }
    }
    /**
     * 检测是否存在摄像头
     *
     * @param context
     * @return
     */
    private boolean checkCameraHardware(Context context) {
        if (context.getPackageManager().hasSystemFeature(PackageManager.FEATURE_CAMERA)) {
            return true;
        } else {
            Toast.makeText(this, "不具备摄像头硬件", Toast.LENGTH_SHORT).show();
            return false;
        }
    }
}

布局activity_main.xml

3.5修改native-lib.cpp

#include 
#include 
#include 
#include 
#include 
#include 
#define TAG "JNI_LOG"
#define LOGE(...)__android_log_print(ANDROID_LOG_ERROR,TAG,__VA_ARGS__)
using namespace cv;
CascadeClassifier cascadeClassifier;
//使用命名空间
void bitmap2Mat(JNIEnv *env, Mat &mat, jobject bitmap);
//mat转成bitmap
void mat2Bitmap(JNIEnv *env, Mat mat, jobject bitmap);
//bitmap转成mat
void bitmap2Mat(JNIEnv *env, Mat &mat, jobject bitmap) {
//Mat里面有个type:CV_8UC4 刚好对上bitmap中的ARGB_8888 CV_8UC2 刚好匹配bitmap中的RGB_565
//1.获取bitmap信息
AndroidBitmapInfo info;
void *pixels;
AndroidBitmap_getInfo(env,bitmap,&info);
//锁定bitmap画布
AndroidBitmap_lockPixels(env,bitmap,&pixels);
//指定mat的宽高和type BGRA
mat.create(info.height,info.width,CV_8UC4);
if(info.format==ANDROID_BITMAP_FORMAT_RGBA_8888){
//对应的mat应该是CV_8UC4
Mat temp(info.height,info.width,CV_8UC4,pixels);
//把数据temp复制到mat里面
temp.copyTo(mat);
}else if(info.format==ANDROID_BITMAP_FORMAT_RGB_565){
    //对应的mat应该是CV_8UC2
    Mat temp(info.height,info.width,CV_8UC2,pixels);
    //上面mat创建的是CV_8UC4 要改为CV_8UC2  CV_8UC2数据拷贝到CV_8UC4
    cvtColor(temp,mat,COLOR_BGR5652BGRA);
}
//其他需要自己去转
//解锁画布
AndroidBitmap_unlockPixels(env,bitmap);
}
extern "C"
JNIEXPORT jint JNICALL
Java_com_suoer_ndk_opencvtestapplication_FaceDetection_faceDetectionSaveInfo(JNIEnv *env,
                              jobject thiz,
                              jobject face_bitmap) {
    // TODO: implement faceDetectionSaveInfo()
    //检测人脸 opencv有关键的类是Mat,opencv是c和c++写的，只会处理Mat,android里面是Bitmap
    //1.Bitmap转成opencv能操作的c++对象 Mat ,Mat是一个矩阵
    Mat mat;
    bitmap2Mat(env,mat,face_bitmap);
    //处理灰度opencv 处理灰度图 提高效率,一般所有的操作都会对齐进行处理
    Mat gray_mat;
    cvtColor(mat,gray_mat,COLOR_BGRA2GRAY);
    //再次处理直方均衡补偿
    Mat equalize_mat;
    equalizeHist(gray_mat,equalize_mat);
    //识别人脸 当然我们可以直接用彩色图去做，识别人脸要加载人脸分类器文件
    std::vector faces;
    cascadeClassifier.detectMultiScale(equalize_mat,faces,1.1,5);
    LOGE("人脸个数:%d",faces.size());
    if(faces.size()!=1){
        return -1;
    }
        Rect faceRect=faces[0];
        //在人脸部分画个图
        rectangle(mat,faceRect,Scalar(255,155,155),8);
        //把mat 放到bitmap中 图片展示出来
        //mat2Bitmap(env,mat,face_bitmap);
        //保存人脸信息 Mat,图片
        Mat face_info_mat(equalize_mat,faceRect);
        //保存face_info_mat
        mat2Bitmap(env,face_info_mat,face_bitmap);
        //mat2Bitmap(env,equalize_mat,face_bitmap);

    //保存人脸信息
    return 0;
}
void mat2Bitmap(JNIEnv *env, Mat mat, jobject bitmap) {
//Mat里面有个type:CV_8UC4 刚好对上bitmap中的ARGB_8888 CV_8UC2 刚好匹配bitmap中的RGB_565
//1.获取bitmap信息
    AndroidBitmapInfo info;
    void *pixels;
    AndroidBitmap_getInfo(env,bitmap,&info);
//锁定bitmap画布
    AndroidBitmap_lockPixels(env,bitmap,&pixels);
    if(info.format==ANDROID_BITMAP_FORMAT_RGBA_8888){
//对应的mat应该是CV_8UC4
        Mat temp(info.height,info.width,CV_8UC4,pixels);
        if(mat.type()==CV_8UC4){
            mat.copyTo(temp);
        }else if(mat.type()==CV_8UC2){
            cvtColor(mat,temp,COLOR_BGR5652BGRA);
        }
        else if(mat.type()==CV_8UC1){//灰度mat
            cvtColor(mat,temp,COLOR_GRAY2BGRA);
        }
    }else if(info.format==ANDROID_BITMAP_FORMAT_RGB_565){
        //对应的mat应该是CV_8UC2
        Mat temp(info.height,info.width,CV_8UC2,pixels);
        if(mat.type()==CV_8UC4){
            cvtColor(mat,temp,COLOR_BGRA2BGR565);
        }else if(mat.type()==CV_8UC2){
            mat.copyTo(temp);
        }
        else if(mat.type()==CV_8UC1){//灰度mat
            cvtColor(mat,temp,COLOR_GRAY2BGR565);
        }
    }
//其他需要自己去转
//解锁画布
    AndroidBitmap_unlockPixels(env,bitmap);
}
extern "C"
JNIEXPORT jboolean JNICALL
Java_com_suoer_ndk_opencvtestapplication_FaceDetection_loadCascade(JNIEnv *env, jobject thiz,
                    jstring file_path) {
    // TODO: implement loadCascade()
    const char *filePath=env->GetStringUTFChars(file_path,0);
    bool load=cascadeClassifier.load(filePath);
    env->ReleaseStringUTFChars(file_path,filePath);
    return load;
}

运行app至手机设备出现如下图所示错误

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第19张

error: undefined reference to 'AndroidBitmap_getInfo'

解决方式修改CMakeLists.txt

Android基于opencv4.6.0实现人脸识别功能，基于opencv4.6.0的Android人脸识别功能实现第20张

target_link_libraries( # Specifies the target library.
                       native-lib opencv-lib
                       #加入该依赖库
                       jnigraphics
                       # Links the target library to the log library
                       # included in the NDK.
                       ${log-lib} )

CMakeLists.txt内容如下：

# For more information about using CMake with Android Studio, read the
# documentation: https://d.android.com/studio/projects/add-native-code.html
# Sets the minimum version of CMake required to build the native library.
cmake_minimum_required(VERSION 3.10.2)
# Declares and names the project.
project("opencvtestapplication")
#需要引入我们头文件，以这个配置的目录为基准
include_directories(${CMAKE_SOURCE_DIR}/../jni/include)
# Creates and names a library, sets it as either STATIC
# or SHARED, and provides the relative paths to its source code.
# You can define multiple libraries, and CMake builds them for you.
# Gradle automatically packages shared libraries with your APK.
add_library( # Sets the name of the library.
             native-lib
             # Sets the library as a shared library.
             SHARED
             # Provides a relative path to your source file(s).
             native-lib.cpp )
# 添加opencv的库
add_library(
        opencv-lib
        SHARED
        IMPORTED)
set_target_properties(
        opencv-lib
        PROPERTIES IMPORTED_LOCATION
        ${CMAKE_SOURCE_DIR}/../jni/armeabi-v7a/libopencv_java4.so)
# Searches for a specified prebuilt library and stores the path as a
# variable. Because CMake includes system libraries in the search path by
# default, you only need to specify the name of the public NDK library
# you want to add. CMake verifies that the library exists before
# completing its build.
find_library( # Sets the name of the path variable.
              log-lib
              # Specifies the name of the NDK library that
              # you want CMake to locate.
              log )
# Specifies libraries CMake should link to your target library. You
# can link multiple libraries, such as libraries you define in this
# build script, prebuilt third-party libraries, or system libraries.
target_link_libraries( # Specifies the target library.
                       native-lib opencv-lib
                       #加入该依赖库
                       jnigraphics
                       # Links the target library to the log library
                       # included in the NDK.
                       ${log-lib} )

其他详细内容可见Demo。