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  • HSV颜色识别demo

    HSV(Hue, Saturation, Value)色彩空间是一种区别与RGB的表示形式。其模型可视为一个倒立的棱锥或圆锥。

    其中H为色调,用角度度量,取值范围为0°~360°,从红色开始按逆时针方向计算,红色为0°,绿色为120°,蓝色为240°。它们的补色是:黄色为60°,青色为180°,品红为300°;

    S为饱和度,饱和度S表示颜色接近光谱色的程度。一种颜色,可以看成是某种光谱色与白色混合的结果。其中光谱色所占的比例愈大,颜色接近光谱色的程度就愈高,颜色的饱和度也就愈高。饱和度高,颜色则深而艳。光谱色的白光成分为0,饱和度达到最高。通常取值范围为0%~100%,值越大,颜色越饱和。

    V为亮度,明度表示颜色明亮的程度,对于光源色,明度值与发光体的光亮度有关;对于物体色,此值和物体的透射比或反射比有关。通常取值范围为0%(黑)到100%(白)。

    下面是一个比较直观的HSV表示图

    HSV色彩空间常用与选取颜色或图像编辑,下面是发现的一个比较有趣的小demo是关于用HSV进行肤色识别的demo

    #include<opencv2/core/core.hpp>
    #include<opencv2/imgproc/imgproc.hpp>
    #include<opencv2/highgui/highgui.hpp>
    #include<iostream>
    
    using namespace cv;
    using namespace std;
    
    int main(int argc, char** argv)
    {
    	VideoCapture cap(0); //capture the video from web cam  
    
    	if (!cap.isOpened())  // if not success, exit program  
    	{
    		cout << "Cannot open the web cam" << endl;
    		return -1;
    	}
    
    	namedWindow("Control", CV_WINDOW_NORMAL); //create a window called "Control"  
    
    	int iLowH = 0;
    	int iHighH = 0;
    
    	int iLowS = 0;
    	int iHighS = 0;
    
    	int iLowV = 0;
    	int iHighV = 0;
    
    	//Create trackbars in "Control" window  
    	cvCreateTrackbar("LowH", "Control", &iLowH, 359); //Hue (0 - 359)  
    	cvCreateTrackbar("HighH", "Control", &iHighH, 259);
    
    	cvCreateTrackbar("LowS", "Control", &iLowS, 255); //Saturation (0 - 255)  
    	cvCreateTrackbar("HighS", "Control", &iHighS, 255);
    
    	cvCreateTrackbar("LowV", "Control", &iLowV, 255); //Value (0 - 255)  
    	cvCreateTrackbar("HighV", "Control", &iHighV, 255);
    
    	while (true)
    	{
    		Mat imgOriginal;
    
    		bool bSuccess = cap.read(imgOriginal); // read a new frame from video  
    
    		if (!bSuccess) //if not success, break loop  
    		{
    			cout << "Cannot read a frame from video stream" << endl;
    			break;
    		}
    
    		Mat imgHSV;
    		vector<Mat> hsvSplit;
    		cvtColor(imgOriginal, imgHSV, COLOR_BGR2HSV); //Convert the captured frame from BGR to HSV  
    
    		// hsv[2] 是v通道 做亮度均衡
    		split(imgHSV, hsvSplit);
    		equalizeHist(hsvSplit[2], hsvSplit[2]);
    		merge(hsvSplit, imgHSV);
    		Mat imgThresholded;
    
    		inRange(imgHSV, Scalar(iLowH, iLowS, iLowV), Scalar(iHighH, iHighS, iHighV), imgThresholded); //Threshold the image  
    
    		//open (remove noise)  
    		Mat element = getStructuringElement(MORPH_RECT, Size(5, 5));
    		morphologyEx(imgThresholded, imgThresholded, MORPH_OPEN, element);
    
    		//close (connect connected-component)  
    		morphologyEx(imgThresholded, imgThresholded, MORPH_CLOSE, element);
    
    		imshow("Thresholded Image", imgThresholded); //show the thresholded image  
    		imshow("Original", imgOriginal); //show the original image  
    
    		char key = (char)waitKey(300);
    		if (key == 27)
    			break;
    	}
    
    	return 0;
    
    }
    

    调整HSV值可以大体检测到人体肤色部位如脸

    代码来自:http://blog.csdn.NET/zwhlxl/article/details/46381353

      

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  • 原文地址:https://www.cnblogs.com/klitech/p/5953059.html
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