Android OpenCv进行图片比对

OpenCv 对于图片有很多的处理方式，现在我想要实现俩张图片的比对。

首先要知道做个需要那些步骤：

（1）加载俩张图片

（2）将两张图片转换为Mat矩阵

（3）把Mat矩阵的type转换为Cv_8uc1类型，然后转换为Cv_32F，

因为在c++代码中会判断他的类型。

（4）通过OpenCv 来进行俩个矩阵的比较（俩个矩阵必须一样大小的高宽）

我使用的比较类型是Imgproc.CV_COMP_CORREL，

double target = Imgproc.compareHist(mat, mat2, Imgproc.CV_COMP_CORREL);

这个target的值越大那么也就是说相似度越高，如果完全一样就是1.0     。

效果图：


思路就是这样，看看代码的实现：

package com.example.opencv_comparepic;

import java.util.Arrays;

import org.opencv.android.BaseLoaderCallback;
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.MatOfFloat;
import org.opencv.core.MatOfInt;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.imgproc.Imgproc;

import android.os.Bundle;
import android.app.Activity;
import android.graphics.Bitmap;
import android.graphics.BitmapFactory;
import android.util.Log;
import android.view.Menu;
import android.view.View;
import android.view.View.OnClickListener;
import android.widget.Button;
import android.widget.ImageView;
import android.widget.Toast;

public class MainActivity extends Activity  implements OnClickListener{
public static final String TAG = "OpenCv_compare";
private Bitmap mBitmap1,mBitmap2;
private ImageView mIv_ImageView1,mIv_ImageView2;
private Button mBtn_compare;
private BaseLoaderCallback callback = new BaseLoaderCallback(this) {
@Override
public void onManagerConnected(int status) {
super.onManagerConnected(status);
switch (status) {
case BaseLoaderCallback.SUCCESS:

break;

default:
break;
}
}
};
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
init();
}

public void init(){
mBitmap1 = BitmapFactory.decodeResource(getResources(), R.drawable.b);
mBitmap2 = BitmapFactory.decodeResource(getResources(), R.drawable.c);
mIv_ImageView1 = (ImageView)findViewById(R.id.iv_img1);
mIv_ImageView2 = (ImageView)findViewById(R.id.iv_img2);
mBtn_compare = (Button)findViewById(R.id.btn_compare);
mIv_ImageView1.setImageBitmap(mBitmap1);
mIv_ImageView2.setImageBitmap(mBitmap2);
mBtn_compare.setOnClickListener(this);
}

@Override
public void onClick(View v) {
Mat mat1 = new Mat();
Mat mat2 = new Mat();
Mat mat11 = new Mat();
Mat mat22 = new Mat();
Utils.bitmapToMat(mBitmap1, mat1);
Utils.bitmapToMat(mBitmap2, mat2);
Imgproc.cvtColor(mat1, mat11, Imgproc.COLOR_BGR2GRAY);
Imgproc.cvtColor(mat2, mat22, Imgproc.COLOR_BGR2GRAY);
comPareHist(mat11, mat22);
}

private Mat                  mMat0;
private MatOfInt             mChannels[];
private MatOfInt             mHistSize;
private int                  mHistSizeNum = 25;
private MatOfFloat           mRanges;
private Scalar               mColorsRGB[];
private Point                mP1;
private Point                mP2;
private float                mBuff[];
public Mat procSrc2GrayJni(Mat srcMat,int type) {
Mat grayMat = new Mat();
Imgproc.cvtColor(srcMat, grayMat, type);//转换为灰度图
// Imgproc.HoughCircles(rgbMat, gray,Imgproc.CV_HOUGH_GRADIENT, 1, 18);
// //霍夫变换找园
mChannels = new MatOfInt[] { new MatOfInt(0), new MatOfInt(1), new MatOfInt(2) };
mBuff = new float[mHistSizeNum];
mHistSize = new MatOfInt(mHistSizeNum);
mRanges = new MatOfFloat(0f, 256f);
mMat0  = new Mat();
mColorsRGB = new Scalar[] { new Scalar(200, 0, 0, 255), new Scalar(0, 200, 0, 255), new Scalar(0, 0, 200, 255) };
mP1 = new Point();
mP2 = new Point();

Mat rgba = srcMat;
Size sizeRgba = rgba.size();
Mat hist = new Mat(); //转换直方图进行绘制
int thikness = (int) (sizeRgba.width / (mHistSizeNum + 10) / 5);
if(thikness > 5) thikness = 5;
int offset = (int) ((sizeRgba.width - (5*mHistSizeNum + 4*10)*thikness)/2);
// RGB
for(int c=0; c<3; c++) {
Imgproc.calcHist(Arrays.asList(rgba), mChannels[c], mMat0, hist, mHistSize, mRanges);
Core.normalize(hist, hist, sizeRgba.height/2, 0, Core.NORM_INF);
hist.get(0, 0, mBuff);
for(int h=0; h<mHistSizeNum; h++) {
mP1.x = mP2.x = offset + (c * (mHistSizeNum + 10) + h) * thikness;
mP1.y = sizeRgba.height-1;
mP2.y = mP1.y - 2 - (int)mBuff[h];
Core.line(rgba, mP1, mP2, mColorsRGB[c], thikness);
}
}

return rgba;
}
/**
* 比较来个矩阵的相似度
* @param srcMat
* @param desMat
*/
public void comPareHist(Mat srcMat,Mat desMat){

srcMat.convertTo(srcMat, CvType.CV_32F);
desMat.convertTo(desMat, CvType.CV_32F);
double target = Imgproc.compareHist(srcMat, desMat, Imgproc.CV_COMP_CORREL);
Log.e(TAG, "相似度 ：   ==" + target);
Toast.makeText(this, "相似度 ：   ==" + target, 1000).show();
}

@Override
protected void onResume() {
super.onResume();
// 通过OpenCV引擎服务加载并初始化OpenCV类库，所谓OpenCV引擎服务即是
// OpenCV_2.4.9.2_Manager_2.4_*.apk程序包，存在于OpenCV安装包的apk目录中
OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_2_4_9, this,
callback);
}
}

可以比较俩张照片的相似度的话那么就可以来进行类似人脸识别然后进行解锁的功能，以后可以用试试看能不能。

http://download.csdn.net/detail/u012808234/9419849