7.MTX20开发板Android Studio+车牌识别算法解析（1）

时间：10-02 整理：3721RD 点击：

首先说明所有车牌识别算法，我都是参考其他人的文章加上自己的一点点理解，希望通过这些文章让自己对车牌的原理、算法，Android版本实现、Android Studio的使用，Opencv一些变量、函数和调用库等有一些了解。因为目前车牌识别的整体算法尚未完全搞明白，所以先说说自己的一些研究后面在整体总结。【EasyPR,特意感谢其作者和其他贡献者。】
一）Android Studio2.2.2上加载Opencv库开发NDK。
第一步：新建工程app目录下build.gradle文件中添加下面的代码

sourceSets {
main {
jniLibs.srcDirs=['/home/gzh/AndroidStudioProjects/MyPlateLocate/app/src/main/opencv310_libs']
}
}

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第二步：新建工程app目录下CMakeLists.txt文件中添加下面的代码，注意路径要修改为自己使用的路径，也要创建对应的目录和文件。

# Sets the minimum version of CMake required to build the native
# library. You should either keep the default value or only pass a
# value of 3.4.0 or lower.
cmake_minimum_required(VERSION 3.4.1)
#
set(pathToProject ~/AndroidStudioProjects/MyPlateLocate)
#OpenCV-android-sdk
set(pathToOpenCv ~/linux-tools/OpenCV-android-sdk)
#支持-std=gnu++11
set(CMAKE_VERBOSE_MAKEFILE on)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=gnu++11")
include_directories(${pathToOpenCv}/sdk/native/jni/include)
include_directories(${pathToProject}//app/src/main/cpp/platelocate/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 it for you.
# Gradle automatically packages shared libraries with your APK.
add_library( # Sets the name of the library.
native-lib
#lib_opencv
# Sets the library as a shared library.
SHARED
# Provides a relative path to your source file(s).
# Associated headers in the same location as their source
# file are automatically included.
src/main/cpp/platelocate/src/platelocate.cpp
src/main/cpp/native-lib.cpp
)
add_library( lib_opencv SHARED IMPORTED )
#引入libopencv_java3.so
set_target_properties(lib_opencv PROPERTIES IMPORTED_LOCATION ${pathToProject}/app/src/main/opencv310_libs/${ANDROID_ABI}/libopencv_java3.so)
# Searches for a specified prebuilt library and stores the path as a
# variable. Because system libraries are included 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 the
# build script, prebuilt third-party libraries, or system libraries.
target_link_libraries( # Specifies the target library.
native-lib
# Links the target library to the log library
# included in the NDK.
${log-lib}
lib_opencv
)

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第三步：添加合适的代码，可以参考下面的灰度图转换实例，不过必须符合自己的实际情况。
二）Opencv Mat类型如何在Java和NDK之间传递。
1）Mat在Java中定义，传递给NDK。
Mat rgbMat = new Mat();
myCvtColor(rgbMat.getNativeObjAddr(), grayMat.getNativeObjAddr(), COLOR_RGB2GRAY);

2）Mat在Java中获取，传递给Java。
Mat& mGr = *(Mat*)imageGray;
Mat& mRgb = *(Mat*)faces;
3）在NDK中创建，然后作为函数返回值返回 ************方法未经验证
Mat *hist = new Mat();
// ...
return (jlong) hist;
此时Java中也要做相应转换才可以使用
long address = generateHistogram(bitmapMat.nativeObj);
Mat histogram = new Mat(address);************方法未经验证

三）灰度图转换实例
3）PlateRecognizer.java代码实现

package com.example.gzh.myplatelocate;
import android.content.Context;
import android.util.Log;
import org.opencv.core.Mat;
/**
* Created by gzh on 17-2-12.
*/
public class PlateRecognizer {
// Used to load the 'native-lib' library on application startup.
static String TAG = "PlateRecognizer";
static {
System.loadLibrary("native-lib");
// System.loadLibrary("opencv_java3");
}
private Context mContext;
private String mSvmpath = "svm.xml";
private String mAnnpath = "ann.xml";
private boolean mRecognizerInited = false;
private long mRecognizerPtr = 0;
public PlateRecognizer(Context context) {
mContext = context;
mRecognizerPtr = initPR();
if (0 ！= mRecognizerPtr) {
mRecognizerInited = true;
}
}
public void finalize() {
uninitPR(mRecognizerPtr);
mRecognizerPtr = 0;
mRecognizerInited = false;
}
public void my_SobelOper(Mat rgbMat, Mat grayMat, int COLOR_RGB2GRAY) {
Log.i(TAG, "my_SobelOper=1=");
mySobelOper(mRecognizerPtr, rgbMat.getNativeObjAddr(), grayMat.getNativeObjAddr());//rgbMat to gray grayMat
Log.i(TAG, "my_SobelOper=2=");
}
public void my_CvtColor(Mat rgbMat, Mat grayMat, int COLOR_RGB2GRAY) {
Log.i(TAG, "my_CvtColor=1=");
myCvtColor(rgbMat.getNativeObjAddr(), grayMat.getNativeObjAddr(), COLOR_RGB2GRAY);//rgbMat to gray grayMat
Log.i(TAG, "my_CvtColor=2=");
}
/**
* A native method that is implemented by the 'native-lib' native library,
* which is packaged with this application.
*/
public static native String stringFromJNI();
//public static native String validate(long matAddrGr, long matAddrRgba);
//图像处理
private static native void myCvtColor(long thiz, long inputImage, long faces);
public static native int[] getGrayImage(int[] pixels, int w, int h);
public static native long initPR();
public static native long uninitPR(long recognizerPtr);
public static native void mySobelOper(long recognizerPtr, long inputImage, long faces);
}

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4）PlateRecognizer.java函数调用代码

public void procSrc2Gray(){
int nFalg_test = 2;
Mat rgbMat = new Mat();
Mat grayMat = new Mat();
srcBitmap = BitmapFactory.decodeResource(getResources(), R.drawable.heidfk640);
grayBitmap = Bitmap.createBitmap(srcBitmap.getWidth(), srcBitmap.getHeight(), Bitmap.Config.RGB_565);
Utils.bitmapToMat(srcBitmap, rgbMat);//convert original bitmap to Mat, R G B.
if(nFalg_test == 1)
{
String str1 = null;
str1 = String.format("call my_CvtColor rgbMat.channels()=%d", rgbMat.channels());
Log.i(TAG, str1);
mPlateRecognizer.my_CvtColor(rgbMat, grayMat, COLOR_RGB2GRAY);//rgbMat to gray grayMat
// Then convert the processed Mat to Bitmap
Log.i(TAG, "call my_CvtColor sucess...=2=");
}
else {
String str1 = null;
str1 = String.format("call my_SobelOper rgbMat.channels()=%d", rgbMat.channels());
Log.i(TAG, str1);
mPlateRecognizer.my_SobelOper(rgbMat, grayMat, COLOR_RGB2GRAY);//rgbMat to gray grayMat
// Then convert the processed Mat to Bitmap
Log.i(TAG, "call my_SobelOper sucess...=2=");
}
Utils.matToBitmap(grayMat, grayBitmap);
Log.i(TAG, "procSrc2Gray sucess...=3=");
show_image.setImageBitmap(grayBitmap);
Log.i(TAG, "procSrc2Gray sucess...");
}

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5）mySobelOper函数NDK调用

extern "C"
JNIEXPORT void JNICALL
Java_com_example_gzh_myplatelocate_PlateRecognizer_mySobelOper
(JNIEnv * jenv,
jlong thiz,
jlong recognizerPtr,
jlong imageGray, jlong faces)
{
Mat imgData_out;
Mat& mGr = *(Mat*)imageGray;
Mat& mRgb = *(Mat*)faces;
LOGE("=1= Java_com_example_gzh_myplatelocate_PlateRecognizer_mySobelOper");
LOGE("=2= mGr.cols=%d", mGr.cols);
LOGE("=2= mGr.rows=%d", mGr.rows);
LOGE("=2= mGr.dims=%d", mGr.dims);
LOGE("=2= mGr.channels=%d", mGr.channels());
// cv:cvtColor(mGr, mRgb, CV_RGB2GRAY);
//mRgb = mRgb /255.0;
CPlateLocate *pr = (CPlateLocate *)recognizerPtr;
#if 1
<b> pr->sobelOper(mGr, imgData_out, m_GaussianBlurSize, m_MorphSizeWidth,m_MorphSizeHeight);//注意此时会有type==CV_8UC1的错误，尚未解决。</b>
#else
#if 1
pr->cvtgray(mGr, mRgb, CV_RGB2GRAY);
#else
cv:cvtColor(mGr, mRgb, CV_RGB2GRAY);//运行ok
#endif
#endif
LOGE("=2= imgData_out.cols=%d", imgData_out.cols);
LOGE("=2= imgData_out.rows=%d", imgData_out.rows);
imgData_out.dims = 0;
LOGE("=2= imgData_out.dims=%d", imgData_out.dims);
LOGE("=2= imgData_out.channels=%d", imgData_out.channels());
// imgData_out = imgData_out / 255.0;
// imgData_out.copyTo(*hist);
LOGE("=3= imgData_outJava_com_example_gzh_myplatelocate_PlateRecognizer_mySobelOper");
}

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6）mySobelOper函数C++代码代码

int CPlateLocate::sobelOper(const Mat &in, Mat &out, int blurSize, int morphW,int morphH)
{
Mat mat_blur;
LOGE("=1= sobelOper");
mat_blur = in.clone();
GaussianBlur(in, mat_blur, Size(blurSize, blurSize), 0, 0, BORDER_DEFAULT);
LOGE("=2= sobelOper");
Mat mat_gray;
if (mat_blur.channels() == 3)
cvtColor(mat_blur, mat_gray, CV_RGB2GRAY);
else
mat_gray = mat_blur;
LOGE("=3= sobelOper");
int scale = SOBEL_SCALE;
int delta = SOBEL_DELTA;
int ddepth = SOBEL_DDEPTH;
Mat grad_x, grad_y;
Mat abs_grad_x, abs_grad_y;
LOGE("=4= sobelOper");
Sobel(mat_gray, grad_x, ddepth, 1, 0, 3, scale, delta, BORDER_DEFAULT);
convertScaleAbs(grad_x, abs_grad_x);
LOGE("=5= sobelOper");
Mat grad;
addWeighted(abs_grad_x, SOBEL_X_WEIGHT, 0, 0, 0, grad);
Mat mat_threshold;
double otsu_thresh_val =
threshold(grad, mat_threshold, 0, 255, CV_THRESH_OTSU + CV_THRESH_BINARY);
LOGE("=6= sobelOper");
#if 0
out = mat_threshold;
#else
Mat element = getStructuringElement(MORPH_RECT, Size(morphW, morphH));
morphologyEx(mat_threshold, mat_threshold, MORPH_CLOSE, element);
out = mat_threshold;
#endif
LOGE("=71= sobelOper");
return 0;
}

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四）Opencv310帮助文件使用方法http://docs.opencv.org/3.1.0/index.html是opencv310帮助的主页，可以在搜索框中搜索所需关键字，会详细的说明，甚至示例代码。
五）总结
1.上面的实例中为了学习Opencv特意将图片数据通过Mat这样的数据结构传递，其实最好是将文件句柄传递给NDK处理，只返回车牌识别后的信息，这样我们就可以把注意力专注到车牌识别的算法和代码实现上。
2.PlateRecognizer.java文件与MainActivity.java文件放置到一起，可以将PlateRecognizer.java单独编译成一个Java库，而在其他Java文件中调用。
3.下面可以考虑把USB Camera预览的数据传递给NDK部分，将处理过的图像传递回来并显示。

大神，很完整的分享啊

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