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.threshold.global;
011
012/**
013 * <p>
014 * Simple global thresholder which uses the mean pixel value as the threshold. See Sec. 9.1.2 of [1] for additional
015 * details (Eq. 9.10).
016 * </p>
017 * <p>
018 * [1] W. Burger, M.J. Burge, <em>Digital Image Processing &ndash; An Algorithmic Introduction</em>, 3rd ed, Springer
019 * (2022).
020 * </p>
021 *
022 * @author WB
023 * @version 2022/08/01
024 */
025public class MeanThresholder implements GlobalThresholder {
026        
027        public MeanThresholder() {
028        }
029
030        @Override
031        public float getThreshold(int[] h) {
032                // calculate mean of the entire image:
033                int K = h.length;
034                int N = 0;
035                
036                long sum = 0;
037                for (int i = 0; i < K; i++) {
038                        N += h[i];
039                        sum += i * h[i];
040                }
041                
042                int mean = (int) Math.floor((double)sum / N);   // important to use floor for bi-level images
043
044                // count resulting background pixels:
045                int nb = 0;
046                for (int i = 0; i <= mean; i++) {
047                        nb += h[i];
048                }
049                
050                // determine if background or foreground is empty:
051                if (nb < N)
052                        return mean;
053                else
054                        return NoThreshold;     // no threshold found
055        }
056}