[openCV] Color Detection

개발환경

사용툴       : Visual Studio 2013 라이브러리 : openCV library 2.4.10 프로젝트    : Visual C++ console application 개발날짜    : 2015-04-16

출처 및 참고 : OpenCV Tutorial C++

                     OpenCV Document - Eroding and Dilating

void FaceDetection::SkinColor_FaceDetection(const char* filename) {         CvCapture* capture;           capture = cvCaptureFromFile(filename);           assert(capture != NULL);           IplImage* bgr_frame = cvQueryFrame(capture);           CvSize size = cvSize((int)cvGetCaptureProperty(capture, CV_CAP_PROP_FRAME_WIDTH),                               (int)cvGetCaptureProperty(capture, CV_CAP_PROP_FRAME_HEIGHT));           cvNamedWindow("CV_Window", 0);         cvNamedWindow("CV_Window_th", 0);         cvResizeWindow("CV_Window", 2048, 1024);         cvResizeWindow("CV_Window_th", 2048, 1024);           //CvVideoWriter *writer = cvCreateVideoWriter("skinColor.avi", CV_FOURCC('D', 'I', 'V', 'X'), 15, size);           int iLowH = 170;         int iHighH = 179;           int iLowS = 150;         int iHighS = 255;           int iLowV = 60;         int iHighV = 255;           Mat imgTmp;         imgTmp = cvarrToMat(bgr_frame);           //Create a black image with the size as the camera output         Mat imgLines = Mat::zeros(imgTmp.size(), CV_8UC3);;           namedWindow("Control", 0); //create a window called "Control"         cvResizeWindow("Control", 400, 300);           //Create trackbars in "Control" window         createTrackbar("LowH", "Control", &iLowH, 179); //Hue (0 - 179)         createTrackbar("HighH", "Control", &iHighH, 179);           createTrackbar("LowS", "Control", &iLowS, 255); //Saturation (0 - 255)         createTrackbar("HighS", "Control", &iHighS, 255);           createTrackbar("LowV", "Control", &iLowV, 255);//Value (0 - 255)         createTrackbar("HighV", "Control", &iHighV, 255);           int iLastX = -1;         int iLastY = -1;                 //while (true)         while ((bgr_frame = cvQueryFrame(capture)) != NULL)         {                Mat imgOriginal;                Mat imgHSV;                Mat imgThresholded;                  imgOriginal = cvarrToMat(bgr_frame); // read a new frame from video                               cvtColor(imgOriginal, imgHSV, COLOR_BGR2HSV); //Convert the captured frame from BGR to HSV                //Threshold the image                inRange(imgHSV, Scalar(iLowH, iLowS, iLowV), Scalar(iHighH, iHighS, iHighV), imgThresholded);                   //morphological opening (remove small objects from the foreground)                erode(imgThresholded, imgThresholded, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));                dilate(imgThresholded, imgThresholded, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));                  //morphological closing (fill small holes in the foreground)                dilate(imgThresholded, imgThresholded, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));                erode(imgThresholded, imgThresholded, getStructuringElement(MORPH_ELLIPSE, Size(5, 5)));                  imshow("CV_Window_th", imgThresholded); //show the thresholded image                imshow("CV_Window", imgOriginal); //show the original image                  //wait for 'esc' key press for 30ms. If 'esc' key is pressed, break loop                if (waitKey(30) == 27)                 {                        cout << "esc key is pressed by user" << endl;                        break;                }         } }

결과화면

HSV 영역을 좀 넓게 잡았더니 피부색 뿐만 아니라 비슷한 영역도 검출함.

control window에서 좀더 조절하면 오류범위를 좁힐 수 있을 듯 함.