/* * Copyright (c) 2011-2016, Peter Abeles. All Rights Reserved. * * This file is part of BoofCV (http://boofcv.org). * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package boofcv.alg.fiducial.calib.chess; import boofcv.abst.filter.binary.InputToBinary; import boofcv.alg.filter.binary.BinaryImageOps; import boofcv.alg.shapes.polygon.BinaryPolygonDetector; import boofcv.alg.shapes.polygon.RefineBinaryPolygon; import boofcv.struct.image.GrayU8; import boofcv.struct.image.ImageGray; import georegression.struct.point.Point2D_F64; import java.util.List; /** * <p> * Detects calibration points inside a chessboard calibration target. The image is first the image * is thresholded to create a binary image for square detection, then the binary image is eroded to make sure * the squares don't touch. After that {@link DetectChessSquarePoints} is called and it detects and sorts * the squares. * </p> * <p> * The found control points are ensured to be returned in a row-major format with the correct number of rows and columns, * with a counter clockwise ordering. Note that when viewed on the monitor this will appear to be clockwise because * the y-axis points down. If there are multiple valid solution then the solution with the (0,0) grid point closest * top the origin is selected. * </p> * <center> * <img src="doc-files/chessboard.jpg"/> * </center> * Example of a 7 by 5 grid; row, column. * * @author Peter Abeles */ public class DetectChessboardFiducial<T extends ImageGray> { // detects the chess board private DetectChessSquarePoints<T> findSeeds; // binary images used to detect chess board private GrayU8 binary = new GrayU8(1, 1); private GrayU8 eroded = new GrayU8(1, 1); // description of the grid its detecting private int numRows,numCols; InputToBinary<T> inputToBinary; /** * Configures detection parameters * @param numRows Number of rows in the grid. Target dependent. * @param numCols Number of columns in the grid. Target dependent. * @param maxCornerDistance The maximum distance two square corners can be from each other in pixels */ public DetectChessboardFiducial(int numRows, int numCols, double maxCornerDistance, BinaryPolygonDetector<T> detectorSquare, RefineBinaryPolygon<T> refineLine, RefineBinaryPolygon<T> refineCorner, InputToBinary<T> inputToBinary) { this.numRows = numRows; this.numCols = numCols; this.inputToBinary = inputToBinary; findSeeds = new DetectChessSquarePoints<>(numRows, numCols, maxCornerDistance, detectorSquare); detectorSquare.setHelper(new ChessboardPolygonHelper<>(detectorSquare, refineLine, refineCorner)); reset(); } /** * Forgets any past history and resets the detector */ public void reset() { } public boolean process(T gray) { binary.reshape(gray.width, gray.height); eroded.reshape(gray.width, gray.height); inputToBinary.process(gray,binary); // erode to make the squares separated BinaryImageOps.erode8(binary, 1, eroded); return findSeeds.process(gray, eroded); } public DetectChessSquarePoints getFindSeeds() { return findSeeds; } public List<Point2D_F64> getCalibrationPoints() { return findSeeds.getCalibrationPoints().toList(); } public GrayU8 getBinary() { return eroded; } public int getColumns() { return numCols; } public int getRows() { return numRows; } }