#include "processing.h" Processing::Processing(/* args */) { } Processing::~Processing() { } static double angle( Point pt1, Point pt2, Point pt0 ) { double dx1 = pt1.x - pt0.x; double dy1 = pt1.y - pt0.y; double dx2 = pt2.x - pt0.x; double dy2 = pt2.y - pt0.y; return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10); } void Processing::filterReflections(FrameData& frameData) { //Try to filter reflections from the frame data. std::vector indicesToDelete; for(int i = 0; i < frameData.contours.size(); i++) { // First approach: correct contours nearly fill their bounding box. // So delete all contours with an area smaller than 75% of their bounding box double contourArea = cv::contourArea(frameData.contours[i], false); double boundingBoxArea = double(frameData.boundingBoxes[i].width*frameData.boundingBoxes[i].height); double minRatio = 0.75; if(boundingBoxArea/contourArea < minRatio) { indicesToDelete.push_back(i); continue; } // Second approach: The contour should be nearly convex // So delete all contours with an area smaller than 95% of their convex hull. std::vector hull; cv::convexHull(frameData.contours[i], hull); double hullArea = cv::contourArea(hull, false); double minRatioHull = 0.95; if(contourArea/boundingBoxArea < minRatio) { indicesToDelete.push_back(i); continue; } // Third approach: // Calculate the HoughLinesP of the contour. // There should be 4 lines // This one is not really working yet. Rect boundingRect = cv::boundingRect(frameData.contours[i]); Point offset(-boundingRect.x, -boundingRect.y); Mat contourMat = Mat::zeros(frameData.boundingBoxes[i].height, frameData.boundingBoxes[i].width, CV_8UC1); drawContours(contourMat, frameData.contours, i, Scalar(255,255,255), 1, 8, noArray(), 0, offset); std::vector linesP; HoughLinesP(contourMat, linesP, 1, CV_PI/180, 20, 10, 5 ); //imshow("Some window", contourMat); if(linesP.size() < 4) { //indicesToDelete.push_back(i); //continue; //std::cout << linesP.size(); } } //reverse the vector with the indices so the order isn't messed up when deleting: std::reverse(indicesToDelete.begin(), indicesToDelete.end()); for(int index : indicesToDelete) { frameData.boundingBoxes.erase(frameData.boundingBoxes.begin() + index); frameData.contours.erase(frameData.contours.begin() + index); frameData.leftEdges.erase(frameData.leftEdges.begin() + index); frameData.middlePoints.erase(frameData.middlePoints.begin() + index); } return; } void Processing::processImage(Mat& inputPicture, int thresholdBinary, int gaussKernelSize, int thresholdCanny1, int thresholdCanny2, int apertureSizeCanny) { //Idea here is: Processing module consists of two methods: // One (this) to do all kinds of stuff to the picture (grayscale conversion, threshold, gauss etc etc) // And one (the other one) to segment the lines. // No return value here as the input is passed by reference -> directly modified. cvtColor(inputPicture, inputPicture, COLOR_BGR2GRAY); GaussianBlur(inputPicture, inputPicture, Size(gaussKernelSize, gaussKernelSize), 0); threshold(inputPicture, inputPicture, thresholdBinary, 255, THRESH_BINARY); //Perform a opening Mat kernel(5,5, CV_8UC1,1); morphologyEx(inputPicture, inputPicture, 2, kernel); } FrameData Processing::calculateLineSegments(const Mat& inputPicture, const cv::Rect& roi) { FrameData data; cv::findContours(inputPicture, data.contours, RETR_LIST, CHAIN_APPROX_SIMPLE); //Delete the areas that are too small auto iterator = data.contours.begin(); while(iterator != data.contours.end()) { if (contourArea(*iterator) < 3500) { iterator = data.contours.erase(iterator); } else { Rect boundingBox = boundingRect(*iterator); boundingBox.x += roi.x; boundingBox.y += roi.y; data.boundingBoxes.push_back(boundingBox); data.middlePoints.push_back(Point(boundingBox.x+boundingBox.width/2, boundingBox.y+boundingBox.height/2)); data.leftEdges.push_back(Point(boundingBox.x, boundingBox.y+boundingBox.height/2)); ++iterator; } } return data; }