本文主要是介绍皮肤检测及对检测到皮肤单独校色 （基于自动白平衡），希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！
原理见前几篇博客，修改修改可以做美颜的程序直接贴代码：
/*对照片中的皮肤单独进行较色，然后塞进原始图片作为输出*/
/*包含皮肤的检测、皮肤的校正两步*/
/*单张照片测试效果不错，但对于一百多张照片，结果还是有偏差，这种单独校正然后再用于贴图的方法 行不通*/
/*时间:2015.8.24*/
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/face.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <iostream>
#include <vector> using namespace std;
using namespace cv;
double baidianave(Mat frame,int n)
{ int a[256];for (int i=0;i<256;i++){a[i]=0;}double sum=0;double ave;for (int i=0;i<n;i++){int d=frame.at<double>(0,i);a[d]++;}int n0=255;for (int k=255;k>0;k--){sum+=a[k];if (sum>frame.rows*frame.cols/25){break;}n0--;}sum=0;for (int i=n0;i<256;i++){sum+=a[i]*i;}ave=sum/(frame.rows*frame.cols/25);return ave;
}
double baidianave(Mat frame)
{ int a[256];
//cvZero(a);for (int i=0;i<256;i++){a[i]=0;}double sum=0;double ave;for (int i=0;i<frame.rows;i++){for (int j=0;j<frame.cols;j++){int d=(int)frame.at<uchar>(i,j);a[d]++;}}int n0=255;for (int k=255;k>0;k--){sum+=a[k];if (sum>frame.rows*frame.cols/25){break;}n0--;}sum=0;for (int i=n0;i<256;i++){sum+=a[i]*i;}ave=sum/(frame.rows*frame.cols/25);return ave;}Mat input_image;
Mat output_mask;
Mat output_image;
Mat mask; int main(int argc,char *argv[])
{ if (2 != argc) {cout << "Please enter the image list!" <<endl;return -1;}vector<string> file_names;FILE *file_list = fopen(argv[1],"r");char buf[255];memset(&buf,0,sizeof(buf));while(fgets(buf,255,file_list)){if(buf[strlen(buf)-1] == '\n') buf[strlen(buf)-1] = '\0';file_names.push_back(string(buf));}fclose(file_list);int count = file_names.size();Mat skinCrCbHist = Mat::zeros(Size(256, 256), CV_8UC1); ellipse(skinCrCbHist, Point(113, 155.6), Size(25,12), -20, 0.0, 360.0, Scalar(255, 255, 255), -1); Mat element = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1) ); for(int i=0; i<count; i++){ string img_nm = file_names[i];string img_mask = "mask" + img_nm;int pos = img_nm.rfind('.');string img_fmt = img_nm.substr(pos+1);if("jpg" != img_fmt){cout << "Unknown format: " << img_fmt << endl;continue;}input_image=imread(img_nm,1); if(input_image.empty()) return 0; Mat ycrcb_image; output_mask = Mat::zeros(input_image.size(), CV_8UC1); cvtColor(input_image, ycrcb_image, CV_BGR2YCrCb); CvScalar s;s.val[0]=0;s.val[1]=0;s.val[2]=255;for(int i = 0; i < input_image.rows; i++) { uchar* p = (uchar*)output_mask.ptr<uchar>(i); Vec3b* ycrcb = (Vec3b*)ycrcb_image.ptr<Vec3b>(i); for(int j = 0; j < input_image.cols; j++) { if(skinCrCbHist.at<uchar>(ycrcb[j][1], ycrcb[j][2]) > 0) {// input_image.at<Vec3b>(i,j)[2]=255;p[j] = 255; }} } // imwrite("test.jpg",input_image);morphologyEx(output_mask,output_mask,MORPH_CLOSE,element); vector< vector<Point> > contours; vector< vector<Point> > filterContours; vector< Vec4i > hierarchy; contours.clear(); hierarchy.clear(); filterContours.clear(); findContours(output_mask, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE); for (size_t i = 0; i < contours.size(); i++) { if (fabs(contourArea(Mat(contours[i]))) > 2000&&fabs(arcLength(Mat(contours[i]),true))>500) filterContours.push_back(contours[i]); } output_mask.setTo(0); drawContours(output_mask, filterContours, -1, Scalar(255,0,0), CV_FILLED); input_image.copyTo(output_image, output_mask); Mat tempimage=Mat::zeros(input_image.size(), CV_8UC3); threshold(output_mask,output_mask,20, 255, THRESH_BINARY);cvtColor(output_mask,output_mask,CV_GRAY2BGR);Mat frame=Mat::zeros(input_image.size(), CV_8UC3); output_image.copyTo(frame);// imshow("frame",frame);// waitKey(0);//cout<<frame.rows<<" "<<frame.cols<<endl;// cvShowImage("处理前图像",frame);int heightyiban=frame.rows;int widthyiban=frame.cols;double Ysum=0;//Y的总和double Cbsum[4]={0,0,0.0};//图像分成四部分，每部分Cb的总和double Crsum[4]={0,0,0,0};//图像分成四部分，每部分Cr的总和double Mb[4],Db[4];//图像分成四部分，每部分Cb的均值和均方差double Mr[4],Dr[3];//Cr的均值和均方差 Mat imageYCrCb = Mat::zeros(frame.size(), CV_8UC3);Mat imageCb = Mat::zeros(frame.size(), CV_8UC1);Mat imageCr = Mat::zeros(frame.size(), CV_8UC1);Mat imageY = Mat::zeros(frame.size(), CV_8UC1);// imageYCrCb = cvCreateImage(cvGetSize(frame),8,3); // imageCb = cvCreateImage(cvGetSize(frame),8,1); // imageCr = cvCreateImage(cvGetSize(frame),8,1); // imageY = cvCreateImage(cvGetSize(frame),8,1); cvtColor(frame,imageYCrCb,CV_BGR2YCrCb); std::vector<cv::Mat>ybr(imageYCrCb.channels());split(imageYCrCb,ybr);// namedWindow("test",0);// imshow("test",ybr[2]);// waitKey(0);//分成三个通道，，，// imageY,imageCr,imageCbMat imageb=Mat::zeros(frame.size(), CV_8UC1);Mat imagec=Mat::zeros(frame.size(), CV_8UC1);ybr[1].copyTo(imageb);ybr[2].copyTo(imagec);Mat savg,sfangcha;//全局scalar 变量用来放平均值和方差meanStdDev(ybr[2],savg,sfangcha);// cvAvgSdv(imageb,&savg,&sfangcha,NULL);// cout<<savg.at<double>(0)<<endl;// cout<<sfangcha.at<double>(0)<<endl;Mb[0]=savg.at<double>(0);cout<<"Mb: "<<Mb[0]<<endl;Db[0]=sfangcha.at<double>(0);//求出第一部分cb的均值和均方差cout<<"Db: "<<Db[0]<<endl;// cvAvgSdv(imagec,&savg,&sfangcha,NULL);meanStdDev(ybr[1],savg,sfangcha);Mr[0]=savg.at<double>(0);cout<<"Mr: "<<Mr[0]<<endl;Dr[0]=sfangcha.at<double>(0);;//求出第一部分cr的均值和均方差cout<<"Dr: "<<Dr[0]<<endl;double b[4],c[4];for (int i=0;i<1;i++){if (Mb[i]<0)//计算mb+db*sign（mb）{ b[i]=Mb[i]+Db[i]*(-1);}elseb[i]=Mb[i]+Db[i];}for (int i=0;i<4;i++){if (Mr[i]<0)//计算1.5*mr+dr*sign（mb）；{c[i]=1.5*Mr[i]+Dr[i]*(-1);}elsec[i]=1.5*Mr[i]+Dr[i];}double Ymax=baidianave(ybr[0]);//下面是对第一部分进行白点的选择Mat Bbaidian=Mat::zeros(1,6000000,CV_64FC1);Mat Gbaidian=Mat::zeros(1,6000000,CV_64FC1);Mat Rbaidian=Mat::zeros(1,6000000,CV_64FC1);//CvScalar s1;int n1=0;cout<<"b[0]: "<<b[0]<<" c[0]: "<<c[0]<<endl;for (int i=0;i<heightyiban;i++){for (int j=0;j<widthyiban;j++){// input_image.at<Vec3b>(i,j)[2]=255if (((ybr[2].at<uchar>(i,j)-b[0])<(1.5*Db[0]))&&((ybr[1].at<uchar>(i,j)-c[0])<(1.5*Dr[0]))){double d1=frame.at<Vec3b>(i,j)[0];Bbaidian.at<double>(0,n1)=d1;double d2=frame.at<Vec3b>(i,j)[1];Gbaidian.at<double>(0,n1)=d2;double d3=frame.at<Vec3b>(i,j)[2];Rbaidian.at<double>(0,n1)=d3;n1++;}}}// cout<<"n1: "<<n1<<endl;double Bave1=baidianave(Bbaidian,n1);double Gave1=baidianave(Gbaidian,n1);double Rave1=baidianave(Rbaidian,n1);cout<<"Bave1: "<<Bave1<<" Gave1: "<<Gave1<<" Rave1: "<<Rave1<<" Ymax: "<<Ymax<<endl;Ymax=Ymax;double Bgain1=Ymax/(Bave1);double Ggain1=Ymax/(Gave1);double Rgain1=Ymax/(Rave1);// CvScalar s1;// cout<<Bgain1<<" "<<Ggain1<<" "<<Rgain1<<endl; // int count_out=0;for (int i=0;i<heightyiban;i++){for (int j=0;j<widthyiban;j++){int tb=Bgain1*frame.at<Vec3b>(i,j)[0];int tg=Ggain1*frame.at<Vec3b>(i,j)[1];int tr=Rgain1*frame.at<Vec3b>(i,j)[2];if (tb>255){tb=255;// count_out++;}if (tg>255){tg=255;// count_out++;}if (tr>255){tr=255;// count_out++;}frame.at<Vec3b>(i,j)[0]=tb;frame.at<Vec3b>(i,j)[1]=tg;frame.at<Vec3b>(i,j)[2]=tr;}}// cout<<count_out<<endl;imwrite("frame.jpg",frame); // cout<<"Finish!"<<endl;imwrite("img_nm1.jpg",input_image); for(int i = 0; i < input_image.rows; i++) { uchar* p = (uchar*)output_mask.ptr<uchar>(i); uchar* p2 = (uchar*)input_image.ptr<uchar>(i); uchar* p3 = (uchar*)frame.ptr<uchar>(i); for(int j = 0; j < 3*input_image.cols; ) { if(p[j] != 0) {// cout<<"p: "<<i<<" "<<j<<" "<<float(p[j])<<endl;// input_image.at<Vec3b>(i,j)[2]=255;p2[j]=0;p2[j] = p3[j++]; // cout<<"B: "<<int (p2[j-1])<<" ";p2[j]=0;p2[j] = p3[j++]; // cout<<"G: "<<int (p2[j-1])<<" ";p2[j]=0;p2[j] = p3[j++]; // cout<<"R: "<<int (p2[j-1])<<endl;;// cout<<"p2: "<<i<<" "<<j<<" "<<float(p2[j])<<endl;}elsej++;} }// Mat tempimage=Mat::zeros(input_image.size(), CV_8UC3); // cvtColor(output_mask,tempimage,CV_GRAY2BGR);// imwrite("output_mask.jpg",output_mask); // imwrite("tempimage.jpg",tempimage); imwrite(img_nm,input_image); imwrite(img_mask,output_image);// imwrite(img_mask,output_mask);// namedWindow("input image",0);// // namedWindow("output mask",0);// namedWindow("output image",0);// imshow("input image", input_image); // imshow("output image", output_image); cout<<"Finish!"<<endl;// output_image.setTo(0); // waitKey(0);} return 0;
}
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