openFrameworks使用ofxOpencv进行肤色检测

由于ofxOpencv里的ofxCVColorImage是RGB格式的，没想到调用getCvImage()函数得到的IplImage居然也是RGB格式，结果害得我一开始肤色检测的结果十分诡异。。。作者也够懒的，这么简单居然也不做个转换！

这个就是调换RB通道的代码：

void testApp::cvRGB_or_BGR(IplImage* src_image, IplImage* dst_image)
{
  if (src_image != NULL && dst_image != NULL)
  {
    uchar* src_data=(uchar *)src_image->imageData;
    uchar* dst_data=(uchar *)dst_image->imageData;
    int step = src_image->widthStep/sizeof(uchar);
    int channels = src_image->nChannels;
    //uchar *b,*g,*r;
    for(int i=0;i<src_image->height;i++)
    {
      for(int j=0;j<src_image->width;j++)
      {
        dst_data[i*step+j*channels + 2] = src_data[i*step+j*channels + 0];  // b
        dst_data[i*step+j*channels + 1] = src_data[i*step+j*channels + 1];  // g
        dst_data[i*step+j*channels] = src_data[i*step+j*channels + 2];    // r
      }
    }
  }
  //cvShowImage("RGB", dst_image);  // debug
}

以下是在网上找到的opencv基于c的肤色检测代码：

void testApp::cvSkinSegment(IplImage* img, IplImage* mask)  // mask是单通道的
{
  CvSize imageSize = cvSize(img->width, img->height);
  IplImage *imgY = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
  IplImage *imgCr = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
  IplImage *imgCb = cvCreateImage(imageSize, IPL_DEPTH_8U, 1);
  IplImage *imgYCrCb = cvCreateImage(imageSize, img->depth, img->nChannels);
  cvCvtColor(img,imgYCrCb,CV_BGR2YCrCb);
  //cvShowImage("img", img);      // debug
  //cvShowImage("YCrCb", imgYCrCb); // debug
  cvSplit(imgYCrCb, imgY, imgCr, imgCb, 0);
  int y, cr, cb, l, x1, y1, value;
  unsigned char *pY, *pCr, *pCb, *pMask;
  pY = (unsigned char *)imgY->imageData;
  pCr = (unsigned char *)imgCr->imageData;
  pCb = (unsigned char *)imgCb->imageData;
  pMask = (unsigned char *)mask->imageData;
  cvSetZero(mask);
  l = img->height * img->width;
  for (int i = 0; i < l; i++)
  {
    y  = *pY;
    cr = *pCr;
    cb = *pCb;
    cb -= 109;
    cr -= 152
      ;
    x1 = (819*cr-614*cb)/32 + 51;
    y1 = (819*cr+614*cb)/32 + 77;
    x1 = x1*41/1024;
    y1 = y1*73/1024;
    value = x1*x1+y1*y1;
    if(y<100) 
      (*pMask)=(value<700) ? 255:0;
    else    
      (*pMask)=(value<850)? 255:0;
    pY++;
    pCr++;
    pCb++;
    pMask++;
  }

  //cvShowImage("mask", mask);  // debug
  cvReleaseImage(&imgY);
  cvReleaseImage(&imgCr);
  cvReleaseImage(&imgCb);
  cvReleaseImage(&imgYCrCb);
  //return mask;
}

我移植的基于c++的肤色检测代码：

void testApp::cvSkinSegment(cv::Mat img, cv::Mat mask)  // mask是单通道的
{
  cv::Size imageSize = img.size();
  cv::Mat imgY, imgCr, imgCb;
  cv::Mat imgYCrCb = cv::Mat(imageSize, CV_8UC3);
  vector<cv::Mat> imgVec;
  cvtColor(img,imgYCrCb,CV_BGR2YCrCb);

  split(imgYCrCb, imgVec);
  imgY = imgVec[0];
  imgCr = imgVec[1];
  imgCb = imgVec[2];
  int y, cr, cb, x1, y1, value;
  uchar *pY, *pCr, *pCb, *pMask;
  mask.zeros(mask.size(), mask.type());

  int nRows = img.rows;
  int nCols = img.cols;
  for (int i = 0; i < nRows; i++)
  {
    pY = imgY.ptr<uchar>(i);
    pCr = imgCr.ptr<uchar>(i);
    pCb = imgCb.ptr<uchar>(i);
    pMask = mask.ptr<uchar>(i);
    for (int j = 0; j<nCols; j++)
    {
      y  = pY[j];
      cr = pCr[j];
      cb = pCb[j];
      cb -= 109;
      cr -= 152;
      x1 = (819*cr - 614*cb)/32 + 51;
      y1 = (819*cr + 614*cb)/32 + 77;
      x1 = x1 * 41/1024;
      y1 = y1 * 73/1024;
      value = x1*x1 + y1*y1;
      if(y<100) 
        (pMask[j])=(value<700) ? 255:0;
      else    
        (pMask[j])=(value<850)? 255:0;
    }

  }

}

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