皮肤检测

今天是地球日，就选了张相关主题的图像做测试

 

第一种：RGB color space

第二种：RG color space

第三种：Ycrcb之cr分量+otsu阈值化

 

还有别的一些模型，效果不太好就不贴了

 

1.rgb model

 // skin region location using rgb limitation
 void SkinRGB(IplImage* rgb,IplImage* _dst)
 {
     assert(rgb->nChannels==3&& _dst->nChannels==3);

     static const int R=2;
     static const int G=1;
     static const int B=0;

     IplImage* dst=cvCreateImage(cvGetSize(_dst),8,3);
     cvZero(dst);

     for (int h=0;h<rgb->height;h++) {
         unsigned char* prgb=(unsigned char*)rgb->imageData+h*rgb->widthStep;
         unsigned char* pdst=(unsigned char*)dst->imageData+h*dst->widthStep;
         for (int w=0;w<rgb->width;w++) {
             if ((prgb[R]>95 && prgb[G]>40 && prgb[B]>20 &&
                 prgb[R]-prgb[B]>15 && prgb[R]-prgb[G]>15/*&&
                 !(prgb[R]>170&&prgb[G]>170&&prgb[B]>170)*/)||//uniform illumination
                 (prgb[R]>200 && prgb[G]>210 && prgb[B]>170 &&
                 abs(prgb[R]-prgb[B])<=15 && prgb[R]>prgb[B]&& prgb[G]>prgb[B])//lateral illumination
                 ) {
                     memcpy(pdst,prgb,3);
             }
             prgb+=3;
             pdst+=3;
         }
     }
     cvCopyImage(dst,_dst);
     cvReleaseImage(&dst);
 }

 

2.rg model

 // skin detection in rg space
 void cvSkinRG(IplImage* rgb,IplImage* gray)
 {
     assert(rgb->nChannels==3&&gray->nChannels==1);

     const int R=2;
     const int G=1;
     const int B=0;

     double Aup=-1.8423;
     double Bup=1.5294;
     double Cup=0.0422;
     double Adown=-0.7279;
     double Bdown=0.6066;
     double Cdown=0.1766;
     for (int h=0;h<rgb->height;h++) {
         unsigned char* pGray=(unsigned char*)gray->imageData+h*gray->widthStep;
         unsigned char* pRGB=(unsigned char* )rgb->imageData+h*rgb->widthStep;
         for (int w=0;w<rgb->width;w++) {
             int s=pRGB[R]+pRGB[G]+pRGB[B];
             double r=(double)pRGB[R]/s;
             double g=(double)pRGB[G]/s;
             double Gup=Aup*r*r+Bup*r+Cup;
             double Gdown=Adown*r*r+Bdown*r+Cdown;
             double Wr=(r-0.33)*(r-0.33)+(g-0.33)*(g-0.33);
             if (g<Gup && g>Gdown && Wr>0.004){
                 *pGray=255;
             }else{
                 *pGray=0;
             }
             pGray++;
             pRGB+=3;
         }
     }

 }

 

3.cr+otsu

 // implementation of otsu algorithm
 // author: onezeros#yahoo.cn
 // reference: Rafael C. Gonzalez. Digital Image Processing Using MATLAB
 void cvThresholdOtsu(IplImage* src, IplImage* dst)
 {
     int height=src->height;
     int width=src->width;

     //histogram
     float histogram[256]={0};
     for(int i=0;i<height;i++) {
         unsigned char* p=(unsigned char*)src->imageData+src->widthStep*i;
         for(int j=0;j<width;j++) {
             histogram[*p++]++;
         }
     }
     //normalize histogram
     int size=height*width;
     for(int i=0;i<256;i++) {
         histogram[i]=histogram[i]/size;
     }

     //average pixel value
     float avgValue=0;
     for(int i=0;i<256;i++) {
         avgValue+=i*histogram[i];
     }

     int threshold;
     float maxVariance=0;
     float w=0,u=0;
     for(int i=0;i<256;i++) {
         w+=histogram[i];
         u+=i*histogram[i];

         float t=avgValue*w-u;
         float variance=t*t/(w*(1-w));
         if(variance>maxVariance) {
             maxVariance=variance;
             threshold=i;
         }
     }

     cvThreshold(src,dst,threshold,255,CV_THRESH_BINARY);
 }

 void cvSkinOtsu(IplImage* src, IplImage* dst)
 {
     assert(dst->nChannels==1&& src->nChannels==3);

     IplImage* ycrcb=cvCreateImage(cvGetSize(src),8,3);
     IplImage* cr=cvCreateImage(cvGetSize(src),8,1);
     cvCvtColor(src,ycrcb,CV_BGR2YCrCb);
     cvSplit(ycrcb,0,cr,0,0);

     cvThresholdOtsu(cr,cr);
     cvCopyImage(cr,dst);
     cvReleaseImage(&cr);
     cvReleaseImage(&ycrcb);
 }

 

原图像

 

rgb model

 

rg model

 

otsu+cr