/* * Copyright (c) 2015 OpenALPR Technology, Inc. * Open source Automated License Plate Recognition [http://www.openalpr.com] * * This file is part of OpenALPR. * * OpenALPR is free software: you can redistribute it and/or modify * it under the terms of the GNU Affero General Public License * version 3 as published by the Free Software Foundation * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU Affero General Public License for more details. * * You should have received a copy of the GNU Affero General Public License * along with this program. If not, see . */ #include "platelines.h" using namespace cv; using namespace std; const float MIN_CONFIDENCE = 0.3; namespace alpr { PlateLines::PlateLines(PipelineData* pipelineData) { this->pipelineData = pipelineData; this->debug = pipelineData->config->debugPlateLines; if (debug) cout << "PlateLines constructor" << endl; } PlateLines::~PlateLines() { } void PlateLines::processImage(Mat inputImage, vector textLines, float sensitivity) { if (this->debug) cout << "PlateLines findLines" << endl; timespec startTime; getTimeMonotonic(&startTime); // Ignore input images that are pure white or pure black Scalar avgPixelIntensity = mean(inputImage); if (avgPixelIntensity[0] >= 252) return; else if (avgPixelIntensity[0] <= 3) return; // Do a bilateral filter to clean the noise but keep edges sharp Mat smoothed(inputImage.size(), inputImage.type()); adaptiveBilateralFilter(inputImage, smoothed, Size(3,3), 45, 45); int morph_elem = 2; int morph_size = 2; Mat element = getStructuringElement( morph_elem, Size( 2*morph_size + 1, 2*morph_size+1 ), Point( morph_size, morph_size ) ); Mat edges(inputImage.size(), inputImage.type()); Canny(smoothed, edges, 66, 133); // Create a mask that is dilated based on the detected characters Mat mask = Mat::zeros(inputImage.size(), CV_8U); for (unsigned int i = 0; i < textLines.size(); i++) { vector > polygons; polygons.push_back(textLines[i].textArea); fillPoly(mask, polygons, Scalar(255,255,255)); } dilate(mask, mask, getStructuringElement( 1, Size( 1 + 1, 2*1+1 ), Point( 1, 1 ) )); bitwise_not(mask, mask); // AND canny edges with the character mask bitwise_and(edges, mask, edges); vector hlines = this->getLines(edges, sensitivity, false); vector vlines = this->getLines(edges, sensitivity, true); for (unsigned int i = 0; i < hlines.size(); i++) this->horizontalLines.push_back(hlines[i]); for (unsigned int i = 0; i < vlines.size(); i++) this->verticalLines.push_back(vlines[i]); // if debug is enabled, draw the image if (this->debug) { Mat debugImgHoriz(edges.size(), edges.type()); Mat debugImgVert(edges.size(), edges.type()); edges.copyTo(debugImgHoriz); edges.copyTo(debugImgVert); cvtColor(debugImgHoriz,debugImgHoriz,CV_GRAY2BGR); cvtColor(debugImgVert,debugImgVert,CV_GRAY2BGR); for( size_t i = 0; i < this->horizontalLines.size(); i++ ) { line( debugImgHoriz, this->horizontalLines[i].line.p1, this->horizontalLines[i].line.p2, Scalar(0,0,255), 1, CV_AA); } for( size_t i = 0; i < this->verticalLines.size(); i++ ) { line( debugImgVert, this->verticalLines[i].line.p1, this->verticalLines[i].line.p2, Scalar(0,0,255), 1, CV_AA); } vector images; images.push_back(debugImgHoriz); images.push_back(debugImgVert); Mat dashboard = drawImageDashboard(images, debugImgVert.type(), 1); displayImage(pipelineData->config, "Hough Lines", dashboard); } if (pipelineData->config->debugTiming) { timespec endTime; getTimeMonotonic(&endTime); cout << "Plate Lines Time: " << diffclock(startTime, endTime) << "ms." << endl; } } vector PlateLines::getLines(Mat edges, float sensitivityMultiplier, bool vertical) { if (this->debug) cout << "PlateLines::getLines" << endl; static int HORIZONTAL_SENSITIVITY = pipelineData->config->plateLinesSensitivityHorizontal; static int VERTICAL_SENSITIVITY = pipelineData->config->plateLinesSensitivityVertical; vector allLines; vector filteredLines; int sensitivity; if (vertical) sensitivity = VERTICAL_SENSITIVITY * (1.0 / sensitivityMultiplier); else sensitivity = HORIZONTAL_SENSITIVITY * (1.0 / sensitivityMultiplier); HoughLines( edges, allLines, 1, CV_PI/180, sensitivity, 0, 0 ); for( size_t i = 0; i < allLines.size(); i++ ) { float rho = allLines[i][0], theta = allLines[i][1]; Point pt1, pt2; double a = cos(theta), b = sin(theta); double x0 = a*rho, y0 = b*rho; double angle = theta * (180 / CV_PI); pt1.x = cvRound(x0 + 1000*(-b)); pt1.y = cvRound(y0 + 1000*(a)); pt2.x = cvRound(x0 - 1000*(-b)); pt2.y = cvRound(y0 - 1000*(a)); if (vertical) { if (angle < 20 || angle > 340 || (angle > 160 && angle < 210)) { // good vertical LineSegment line; if (pt1.y <= pt2.y) line = LineSegment(pt2.x, pt2.y, pt1.x, pt1.y); else line = LineSegment(pt1.x, pt1.y, pt2.x, pt2.y); // Get rid of the -1000, 1000 stuff. Terminate at the edges of the image // Helps with debugging/rounding issues later LineSegment top(0, 0, edges.cols, 0); LineSegment bottom(0, edges.rows, edges.cols, edges.rows); Point p1 = line.intersection(bottom); Point p2 = line.intersection(top); PlateLine plateLine; plateLine.line = LineSegment(p1.x, p1.y, p2.x, p2.y); plateLine.confidence = (1.0 - MIN_CONFIDENCE) * ((float) (allLines.size() - i)) / ((float)allLines.size()) + MIN_CONFIDENCE; filteredLines.push_back(plateLine); } } else { if ( (angle > 70 && angle < 110) || (angle > 250 && angle < 290)) { // good horizontal LineSegment line; if (pt1.x <= pt2.x) line = LineSegment(pt1.x, pt1.y, pt2.x, pt2.y); else line =LineSegment(pt2.x, pt2.y, pt1.x, pt1.y); // Get rid of the -1000, 1000 stuff. Terminate at the edges of the image // Helps with debugging/ rounding issues later int newY1 = line.getPointAt(0); int newY2 = line.getPointAt(edges.cols); PlateLine plateLine; plateLine.line = LineSegment(0, newY1, edges.cols, newY2); plateLine.confidence = (1.0 - MIN_CONFIDENCE) * ((float) (allLines.size() - i)) / ((float)allLines.size()) + MIN_CONFIDENCE; filteredLines.push_back(plateLine); } } } return filteredLines; } Mat PlateLines::customGrayscaleConversion(Mat src) { Mat img_hsv; cvtColor(src,img_hsv,CV_BGR2HSV); Mat grayscale = Mat(img_hsv.size(), CV_8U ); Mat hue(img_hsv.size(), CV_8U ); for (int row = 0; row < img_hsv.rows; row++) { for (int col = 0; col < img_hsv.cols; col++) { int h = (int) img_hsv.at(row, col)[0]; //int s = (int) img_hsv.at(row, col)[1]; int v = (int) img_hsv.at(row, col)[2]; int pixval = pow(v, 1.05); if (pixval > 255) pixval = 255; grayscale.at(row, col) = pixval; hue.at(row, col) = h * (255.0 / 180.0); } } //displayImage(config, "Hue", hue); return grayscale; } }