接上篇博文：视觉检测过程中特征匹配结果容器类<DMatch>判断

紧接上篇博文，顺势将特征匹配的结果进行筛选，并把代码做了实现。

思路是用matches[i].distance判断是否满足条件，由于网上能够查阅到的资料仅仅是将计算得到的匹配特征点用drawMatch()绘制两幅图像的匹配结果，我这里是自己进行了匹配筛选，编译是能够成功的。

double averagematch_dist =0;
    for(int i = 0; i < ptsPairs; i++)
    {
     averagematch_dist = averagematch_dist + good_matches[i].distance / ptsPairs;
    }
    //averagematch = 0.5 * (good_matches[0].distance + good_matches[ptsPairs].distance);
    if(!(good_matches[0].distance < 1.0 &&
       good_matches[ptsPairs].distance < 1.0 &&
       (good_matches[0].distance - averagematch_dist < 0.5 ) &&
        good_matches[ptsPairs].distance - averagematch_dist < 0.5 ))
      continue;
    /*
      double max_dist = 0;
      double min_dist = 100;
      for(int i = 0; i < descriptor1.rows; i++)
      {
        double dist = matches[i].distance;
        if(dist < min_dist)
          min_dist = dist;
       if(dist > max_dist)
          max_dist = dist;
      }//得到匹配结果中的最小距离和最大距离

      //处理匹配结果：判断当前匹配的对象是否为目标，仅根据最大最小匹配距离，能否进行判断？
      if(!(min_dist < 1.0 || (max_dist - min_dist) <  2.0))// matching failed
      {
       //tracking_frame = tracking_frame;
       //body_track_rect = body_track_rect;
      continue;
      }
    */