皮肤检测算法三种，示例与代码

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