OpenCV——肤色检测

一、RGB color space

检测代码如下：

void SkinRGB(IplImage* src,IplImage* dst)
{
    //RGB颜色空间
    //均匀照明：R>95,G>40,B>20,R-B>15,R-G>15,R>B%R
    //侧向照明:R>200,G>210,B>170,R-B<=15,R>B,G>B
        
    int height = src->height, width = src->width, channel = src->nChannels, step = src->widthStep;
    int b = 0, g = 1, r = 2;

    cvZero(dst);
    unsigned char* p_src = (unsigned char*)src->imageData;
    unsigned char* p_dst = (unsigned char*)dst->imageData;
        
    for(int j = 0; j < height; j++){
        for(int i = 0; i < width; i++){
            if((p_src[j*step+i*channel+r] > 95 && p_src[j*step+i*channel+g] > 40 && p_src[j*step+i*channel+b] > 20 && 
                (p_src[j*step+i*channel+r] - p_src[j*step+i*channel+b]) > 15 && (p_src[j*step+i*channel+r] - p_src[j*step+i*channel+g]) > 15) || 
                (p_src[j*step+i*channel+r] > 200 && p_src[j*step+i*channel+g] > 210 && p_src[j*step+i*channel+b] > 170 && 
                (p_src[j*step+i*channel+r] - p_src[j*step+i*channel+b]) <= 15 && p_src[j*step+i*channel+r] > p_src[j*step+i*channel+b] && 
                p_src[j*step+i*channel+g] > p_src[j*step+i*channel+b]))
                p_dst[j*width+i]=255;
        }
    }
}

二、二次多项式模式检测（RG color 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;    
        }    
    }    
}    

三、Ycrcb之cr分量+otsu阈值化

原理：       a.将RGB图像转换到YCrCb颜色空间，提取Cr分量图像           

                b.对Cr做自适应二值化处理（Ostu法）

void cvSkinOtsu(IplImage* src, IplImage* dst)  
{  
    //Cr自适应阈值法  
    //  
  
    IplImage* img_ycrcb=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,3);  
    IplImage* img_cr=cvCreateImage(cvGetSize(src),IPL_DEPTH_8U,1);  
  
    cvCvtColor(src,img_ycrcb,CV_BGR2YCrCb);  
    cvSplit(img_ycrcb,0,img_cr,0,0);  
    cvThresholdOtsu(img_cr,img_cr);  
    cvCopy(img_cr,dst);  
  
    cvReleaseImage(&img_ycrcb);  
    cvReleaseImage(&img_cr);  
}  



void cvThresholdOtsu(IplImage* src, IplImage* dst)  
{  
    int height=src->height,width=src->width,threshold=0;  
    double histogram[256]={0};  
    double average=0.0,max_variance=0.0,w=0.0,u=0.0;  
    IplImage* temp=cvCreateImage(cvGetSize(src),src->depth,1);  
    if(src->nChannels!=1)cvCvtColor(src,temp,CV_BGR2GRAY);  
    else cvCopy(src,temp);  
  
    unsigned char* p_temp=(unsigned char*)temp->imageData;  
  
    //计算灰度直方图  
    //  
    for(int j=0;j<height;j++) {  
        for(int i=0;i<width;i++) {  
            histogram[p_temp[j*width+i]]++;  
        }  
    }  
    for(int i=0;i<256;i++)histogram[i]=histogram[i]/(double)(height*width);  
  
    //计算平局值  
    for(int i=0;i<256;i++)average+=i*histogram[i];  
  
    for(int i=0;i<256;i++) {  
        w+=histogram[i];  
        u+=i*histogram[i];  
  
        double t=average*w-u;    
        double variance=t*t/(w*(1-w));    
        if(variance>max_variance) {    
            max_variance=variance;    
            threshold=i;    
        }    
    }  
    cvThreshold(temp,dst,threshold,255,CV_THRESH_BINARY);  
  
    cvReleaseImage(&temp);  
}

四、OpenCV自带肤色检测类——CvAdaptiveSkinDetector

 通过颜色阈值分割肤色部分，皮肤检测算法是在HSV空间进行。流程如下：

//构造函数
CvAdaptiveSkinDetector(int samplingDivider = 1, int morphingMethod = MORPHING_METHOD_NONE);

/*
参数1：样本采样的间隔，默认情况下为1，即表示不进行降采样
参数2：图形学操作方式，即对用皮肤检测后的图像进行图形学操作。其取值有3种可能——MORPHING_METHOD_ERODE（只进行一次腐蚀操作）；MORPHING_METHOD_ERODE_ERODE（连续进行2次腐蚀操作）；MORPHING_METHOD_ERODE_DILATE（先进行一次腐蚀操作，后进行一次膨胀操作）
*/

virtual void process(IplImage *inputBGRImage, IplImage *outputHueMask);

/*
参数1：需要进行皮肤检测的输入图像
参数2：输出皮肤的掩膜图像——值为1代表该像素为皮肤，值为0代表非皮肤。
*/

PS：这个函数只有opencv的c版本的，因为CvAdaptiveSkinDetector这个类放在opencv源码里的contrib目录里，即表示比较新的但不成熟的算法。

#include <opencvcv.h>  
#include <opencvhighgui.h>  
#include <contribcontrib.hpp>  
#include <corecore.hpp>  
#include <imgprocimgproc.hpp>  
#include<time.h>  
  
int main()  
{ 
    CvCapture* capture=cvCreateCameraCapture(0);  
    cvNamedWindow("Input Video",1);  
    cvNamedWindow("Output Video",1);  
  
    IplImage* img_src=NULL;  
    IplImage* input_img=NULL;  
    IplImage* output_mask=NULL;  
    IplImage* output_img=NULL;  
  
    clock_t start,finish;  
    double duration;  
  
    CvAdaptiveSkinDetector skin_detector(1,CvAdaptiveSkinDetector::MORPHING_METHOD_ERODE_DILATE);    //定义肤色检测算子  
  
    while(1)
   {  
        img_src=cvQueryFrame(capture);  
        if(!img_src) break;  
        cvShowImage("Input Video",img_src);  
        if(input_img==NULL){  
            input_img=cvCreateImage(cvGetSize(img_src),img_src->depth,img_src->nChannels);  
        }  
        cvCopy(img_src,input_img);  
  
        output_img=cvCreateImage(cvGetSize(img_src),img_src->depth,img_src->nChannels);  
        cvZero(output_img);  
  
        if(output_mask==NULL){  
            output_mask=cvCreateImage(cvGetSize(img_src),img_src->depth,1);  
        }  
  
        //肤色检测  
        //  
        start=clock();  
        skin_detector.process(input_img,output_mask);  
        finish=clock();  
        duration=(double)(finish-start)/CLOCKS_PER_SEC;  
        printf("elapsed time :%.0f 毫秒
",duration*1000);   
  
        cvCopy(img_src,output_img,output_mask);  
        cvShowImage("Output Video",output_img);  
  
        char c=cvWaitKey(33);  
        if(c==27)break;  
    }  
  
    cvReleaseCapture(&capture);  
    cvDestroyWindow("Video");  
}  

五、HSV检测

void cvSkinHSV(IplImage* src,IplImage* dst)    
{    
    IplImage* hsv=cvCreateImage(cvGetSize(src),8,3);    
    //IplImage* cr=cvCreateImage(cvGetSize(src),8,1);     
    //IplImage* cb=cvCreateImage(cvGetSize(src),8,1);     
    cvCvtColor(src,hsv,CV_BGR2HSV);    
    //cvSplit(ycrcb,0,cr,cb,0);     
    
    static const int V=2;    
    static const int S=1;    
    static const int H=0;    
    
    //IplImage* dst=cvCreateImage(cvGetSize(_dst),8,3);     
    cvZero(dst);    
    
    for (int h=0;h<src->height;h++) {    
        unsigned char* phsv=(unsigned char*)hsv->imageData+h*hsv->widthStep;    
        unsigned char* psrc=(unsigned char*)src->imageData+h*src->widthStep;    
        unsigned char* pdst=(unsigned char*)dst->imageData+h*dst->widthStep;    
        for (int w=0;w<src->width;w++) {    
            if (phsv[H]>=7&&phsv[H]<=29)    
            {    
                    memcpy(pdst,psrc,3);    
            }    
            phsv+=3;    
            psrc+=3;    
            pdst+=3;    
        }    
    }    
    //cvCopyImage(dst,_dst);     
    //cvReleaseImage(&dst);     
}