OpenCV编程->对比直方图

OpenCv提供了5种对比直方图的方式：CORREL（相关）、CHISQR（卡方）、INTERSECT（相交）、BHATTACHARYYA、EMD（最小工作距离），其中CHISQR速度最快，EMD速度最慢且有诸多限制，但是EMD的效果可能最好。

接下来开始测试一下：

对比函数如下：

#define cvQueryHistValue_3D( hist, idx0, idx1, idx2 )      cvGetReal3D( (hist)->bins, (idx0), (idx1), (idx2) )
//画直方图用
int HistogramBins = 256;
float HistogramRange1[2]={0,255};
float *HistogramRange[1]={&HistogramRange1[0]};

void histemd(IplImage* src,IplImage* src1)
{
   IplImage* hsv = cvCreateImage( cvGetSize(src), 8, 3 );
   IplImage* hsv1 = cvCreateImage( cvGetSize(src), 8, 3 );
   cvCvtColor( src, hsv, CV_BGR2HSV );
   cvCvtColor( src1, hsv1, CV_BGR2HSV );
   IplImage* h_plane = cvCreateImage( cvGetSize(src), 8, 1 );
   IplImage* s_plane = cvCreateImage( cvGetSize(src), 8, 1 );
   IplImage* v_plane = cvCreateImage( cvGetSize(src), 8, 1 );
   IplImage* h_plane1 = cvCreateImage( cvGetSize(src), 8, 1 );
   IplImage* s_plane1 = cvCreateImage( cvGetSize(src), 8, 1 );
   IplImage* v_plane1 = cvCreateImage( cvGetSize(src), 8, 1 );
   IplImage* planes[] = { h_plane, s_plane,v_plane };
   IplImage* planes1[] = { h_plane1, s_plane1,v_plane1 };
    cvSplit( hsv, h_plane, s_plane, v_plane, 0 );
    cvSplit( hsv1, h_plane1, s_plane1, v_plane1, 0 );
   // Build the histogram and compute its contents.
   //计算规模与h_bins*s_bins*v_bins成指数关系，原先 int h_bins = 32, s_bins = 30, v_bins = 8 时，运行半天都没反应
   int h_bins = 8, s_bins = 5, v_bins = 5;
    CvHistogram* hist, *hist1;
   {
      int hist_size[] = { h_bins, s_bins ,v_bins};
      float h_ranges[] = { 0, 180 }; // hue is [0,180]
      float s_ranges[] = { 0, 255 };
      float v_ranges[] = { 0, 255 };
      float* ranges[] = { h_ranges, s_ranges ,v_ranges};
      hist = cvCreateHist(
         3,
         hist_size,
         CV_HIST_ARRAY,
         ranges,
         1
         );
      hist1 = cvCreateHist(
         3,
         hist_size,
         CV_HIST_ARRAY,
         ranges,
         1
         );
   }
   cvCalcHist( planes, hist, 0, 0 ); //Compute histogram
   cvNormalizeHist( hist, 1.0 ); //Normalize it
   cvCalcHist( planes1, hist1, 0, 0 ); //Compute histogram
   cvNormalizeHist( hist1, 1.0 ); //Normalize it  

   CvMat* sig1,*sig2;
   int numrows = h_bins*s_bins*v_bins;  

   sig1 = cvCreateMat(numrows, 4, CV_32FC1);
   sig2 = cvCreateMat(numrows, 4, CV_32FC1);
   int h,s,v;
   for( h = 0; h < h_bins; h++ )
   {
      for( s = 0; s < s_bins; s++ )
      {
         for( v=0; v < v_bins; v++)
         {
            float bin_val = cvQueryHistValue_3D( hist, h, s,v );  

            cvSet2D(sig1,h*s_bins*v_bins + s*v_bins+v,0,cvScalar(bin_val)); //bin value
            cvSet2D(sig1,h*s_bins*v_bins + s*v_bins+v,1,cvScalar(h)); //Coord 1
            cvSet2D(sig1,h*s_bins*v_bins + s*v_bins+v,2,cvScalar(s)); //Coord 2
            cvSet2D(sig1,h*s_bins*v_bins + s*v_bins+v,3,cvScalar(v)); //Coord 3  

            bin_val = cvQueryHistValue_3D( hist1, h, s,v );
            cvSet2D(sig2,h*s_bins*v_bins + s*v_bins+v,0,cvScalar(bin_val)); //bin value
            cvSet2D(sig2,h*s_bins*v_bins + s*v_bins+v,1,cvScalar(h)); //Coord 1
            cvSet2D(sig2,h*s_bins*v_bins + s*v_bins+v,2,cvScalar(s)); //Coord 2
            cvSet2D(sig2,h*s_bins*v_bins + s*v_bins+v,3,cvScalar(v)); //Coord 3  

         }
      }
   }  

   float emd = cvCalcEMD2(sig1,sig2,CV_DIST_L2);
   printf("CV_COMP_EMD ：%3.1f%%",(1-emd)*100);  

   cvNamedWindow( "Source1", 1 );
   cvMoveWindow("Source1", 0, 0);
   cvShowImage( "Source1", src );
   cvNamedWindow( "Source2", 1 );
   cvMoveWindow("Source2", 550, 0);
   cvShowImage( "Source2", src1 );
   cvWaitKey(0);
}

void CompareHist(const char* imagefile1, const char* imagefile2)
{
    IplImage *image1=cvLoadImage(imagefile1, 0);
    IplImage *image2=cvLoadImage(imagefile2, 0);

	IplImage *image3=cvLoadImage(imagefile1,1);
    IplImage *image4=cvLoadImage(imagefile2,1);

    CvHistogram *Histogram1 = cvCreateHist(1, &HistogramBins, CV_HIST_ARRAY,HistogramRange);
    CvHistogram *Histogram2 = cvCreateHist(1, &HistogramBins, CV_HIST_ARRAY,HistogramRange);

    cvCalcHist(&image1, Histogram1);
    cvCalcHist(&image2, Histogram2);

    cvNormalizeHist(Histogram1, 1);
    cvNormalizeHist(Histogram2, 1);

    // CV_COMP_CHISQR,CV_COMP_BHATTACHARYYA这两种都可以用来做直方图的比较，值越小，说明图形越相似
    printf("CV_COMP_CHISQR : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_CHISQR));//卡方
    printf("CV_COMP_BHATTACHARYYA : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_BHATTACHARYYA));

    // CV_COMP_CORREL, CV_COMP_INTERSECT这两种直方图的比较，值越大，说明图形越相似
    printf("CV_COMP_CORREL : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_CORREL));//相关
    printf("CV_COMP_INTERSECT : %.4f\n", cvCompareHist(Histogram1, Histogram2, CV_COMP_INTERSECT));//相交
	 histemd(image3,image4);

}

在主函数里面调用：

 CompareHist("1001.png", "1002.png");

得到如下测试结果：

对于不同图片：

对于做直方图对比，对比图像的颜色背景需要一致，不然就出入很大。

参考：

http://www.cnblogs.com/slysky/archive/2011/10/13/2210745.html

http://blog.csdn.net/nicebooks/article/details/8175002

OpenCV编程->对比直方图,布布扣,bubuko.com