001/*******************************************************************************
002 * This software is provided as a supplement to the authors' textbooks on digital
003 * image processing published by Springer-Verlag in various languages and editions.
004 * Permission to use and distribute this software is granted under the BSD 2-Clause
005 * "Simplified" License (see http://opensource.org/licenses/BSD-2-Clause).
006 * Copyright (c) 2006-2023 Wilhelm Burger, Mark J. Burge. All rights reserved.
007 * Visit https://imagingbook.com for additional details.
008 ******************************************************************************/
009
010package imagingbook.common.corners;
011
012import ij.process.ImageProcessor;
013
014import static imagingbook.common.math.Arithmetic.sqr;
015import static java.lang.Math.sqrt;
016
017
018/**
019 * <p>
020 * This is an implementation of the Shi-Tomasi corner detector, as described in [1]. This class extends
021 * {@link GradientCornerDetector} (where most of the work is done) by defining a specific corner score function and
022 * associated threshold. See Sec. 6.3.1 of [2] for additional details.
023 * </p>
024 * <p>
025 * [1] J. Shi and C. Tomasi. Good features to track. In Proceedings of IEEE Conference on Computer Vision and Pattern
026 * Recognition, CVPR’94, pp. 593–600, Seattle, WA, USA (1994).
027 * <br>
028 * [2] W. Burger, M.J. Burge, <em>Digital Image Processing &ndash; An Algorithmic Introduction</em>, 3rd ed, Springer
029 * (2022).
030 * </p>
031 *
032 * @author WB
033 * @version 2022/03/30
034 */
035public class ShiTomasiCornerDetector extends GradientCornerDetector {
036        
037        public ShiTomasiCornerDetector(ImageProcessor ip, GradientCornerDetector.Parameters params) {
038                super(ip, params);
039        }
040        
041        // --------------------------------------------------------------
042
043        @Override
044        protected float getCornerScore(float A, float B, float C) {
045                double rootExpr = sqr((A - B) / 2) + sqr(C);
046                if (rootExpr < 0) {
047                        return UndefinedScoreValue;
048                }
049                double lambda2 = (A + B) / 2 - sqrt(rootExpr);
050                return (float) lambda2;
051        }
052
053}