本文主要是介绍OpenCV编程-肤色检测，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！
最近搞色彩认知计算，对于肤色检测也是兴趣使然。
我们在处理图像时，首先考虑的就是去噪，但是去噪不仅是去掉噪声，也需要考虑光照对图像造成的噪声，所以如果硬件跟得上的话，可以引入颜色恒常性计算来去噪，之后开始正题吧。
肤色检测说起来很简单，只要是色彩的空间分离，在这个过程中难免有误检，如果对目标能进行有监督的框定，再进行肤色检测，效果应该好很多。
接下来贴代码：
void SkinDetect(IplImage* src,IplImage* dst)
{ // 创建图像头IplImage* hsv = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 3);//用于存图像的个中间变量，是用来分通道用的,分成hsv通道 IplImage* tmpH1 = cvCreateImage( cvGetSize(src), IPL_DEPTH_8U, 1);//通道的中间变量,用于肤色检测的中D间变量 IplImage* tmpS1 = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1); IplImage* tmpH2 = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1); IplImage* tmpS3 = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1); IplImage* tmpH3 = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1); IplImage* tmpS2 = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1); IplImage* H = cvCreateImage( cvGetSize(src), IPL_DEPTH_8U, 1); IplImage* S = cvCreateImage( cvGetSize(src), IPL_DEPTH_8U, 1); IplImage* V = cvCreateImage( cvGetSize(src), IPL_DEPTH_8U, 1); IplImage* src_tmp1=cvCreateImage(cvGetSize(src),8,3); // 高斯模糊 cvSmooth(src,src_tmp1,CV_GAUSSIAN,3,3); //高斯模糊 // hue色度saturation饱和度value纯度 cvCvtColor(src_tmp1, hsv, CV_BGR2HSV );//颜色转换 cvSplit(hsv,H,S,V,0);//分为3个通道 /*********************肤色检测部分·**************/ cvInRangeS(H,cvScalar(26.0,0.0,0,0),cvScalar(34.0,0.0,0,0),tmpH1); cvInRangeS(S,cvScalar(43.0,0.0,0,0),cvScalar(255.0,0.0,0,0),tmpS1); cvAnd(tmpH1,tmpS1,tmpH1,0); // Red Hue with Low Saturation // Hue 0 to 26 degree and Sat 20 to 90 cvInRangeS(H,cvScalar(11.0,0.0,0,0),cvScalar(25.0,0.0,0,0),tmpH2); cvInRangeS(S,cvScalar(43.0,0.0,0,0),cvScalar(255.0,0.0,0,0),tmpS2); cvAnd(tmpH2,tmpS2,tmpH2,0); // Red Hue to Pink with Low Saturation // Hue 340 to 360 degree and Sat 15 to 90 // cvInRangeS(H,cvScalar(170.0,0.0,0,0),cvScalar(180.0,0.0,0,0),tmpH3); // cvInRangeS(S,cvScalar(15.0,0.0,0,0),cvScalar(90.,0.0,0,0),tmpS3); // cvAnd(tmpH3,tmpS3,tmpH3,0); // Combine the Hue and Sat detections // cvOr(tmpH3,tmpH2,tmpH2,0); cvOr(tmpH1,tmpH2,tmpH1,0); cvCopy(tmpH1,dst); int avg,white=0,black=0;CvScalar s;for(int i=0;i<dst->height;i++){for (int j = 0;j<dst->width;j++){s = cvGet2D(dst,i,j);if(s.val[0]==255)white++;elseblack++;}}printf("white = %dn",white);printf("black = %dn",black);cvReleaseImage(&hsv); cvReleaseImage(&tmpH1); cvReleaseImage(&tmpS1); cvReleaseImage(&tmpH2); cvReleaseImage(&tmpS2); cvReleaseImage(&tmpH3); cvReleaseImage(&tmpS3); cvReleaseImage(&H); cvReleaseImage(&S); cvReleaseImage(&V); cvReleaseImage(&src_tmp1);
} 测试图像：
得到的图像虽然不好，相信从代码里面能看到原因。
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