2 * Copyright 2007 Google Inc.
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4 * Licensed under the Apache License, Version 2.0 (the "License");
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5 * you may not use this file except in compliance with the License.
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6 * You may obtain a copy of the License at
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8 * http://www.apache.org/licenses/LICENSE-2.0
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10 * Unless required by applicable law or agreed to in writing, software
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11 * distributed under the License is distributed on an "AS IS" BASIS,
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12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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13 * See the License for the specific language governing permissions and
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14 * limitations under the License.
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17 package com.google.zxing.common;
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20 * <p>Encapsulates logic that estimates the optimal "black point", the luminance value
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21 * which is the best line between "white" and "black" in a grayscale image.</p>
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23 * <p>For an interesting discussion of this issue, see
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24 * <a href="http://webdiis.unizar.es/~neira/12082/thresholding.pdf">http://webdiis.unizar.es/~neira/12082/thresholding.pdf</a>.
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27 * @author srowen@google.com (Sean Owen)
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28 * @author dswitkin@google.com (Daniel Switkin)
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30 public final class BlackPointEstimator {
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32 private BlackPointEstimator() {
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36 * <p>Given an array of <em>counts</em> of luminance values (i.e. a histogram), this method
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37 * decides which bucket of values corresponds to the black point -- which bucket contains the
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38 * count of the brightest luminance values that should be considered "black".</p>
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40 * @param histogram an array of <em>counts</em> of luminance values
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41 * @param biasTowardsWhite values higher than 1.0 suggest that a higher black point is desirable (e.g.
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42 * more values are considered black); less than 1.0 suggests that lower is desirable. Must be greater
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43 * than 0.0; 1.0 is a good "default"
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44 * @return index within argument of bucket corresponding to brightest values which should be
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45 * considered "black"
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47 public static int estimate(int[] histogram, float biasTowardsWhite) {
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49 if (Float.isNaN(biasTowardsWhite) || biasTowardsWhite <= 0.0f) {
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50 throw new IllegalArgumentException("Illegal biasTowardsWhite: " + biasTowardsWhite);
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53 int numBuckets = histogram.length;
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55 // Find tallest peak in histogram
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57 int firstPeakSize = 0;
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58 for (int i = 0; i < numBuckets; i++) {
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59 if (histogram[i] > firstPeakSize) {
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61 firstPeakSize = histogram[i];
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65 // Find second-tallest peak -- well, another peak that is tall and not
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66 // so close to the first one
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68 int secondPeakScore = 0;
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69 for (int i = 0; i < numBuckets; i++) {
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70 int distanceToBiggest = i - firstPeak;
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71 // Encourage more distant second peaks by multiplying by square of distance
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72 int score = histogram[i] * distanceToBiggest * distanceToBiggest;
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73 if (score > secondPeakScore) {
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75 secondPeakScore = score;
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79 // Put firstPeak first
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80 if (firstPeak > secondPeak) {
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81 int temp = firstPeak;
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82 firstPeak = secondPeak;
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86 // Find a valley between them that is low and closer to the white peak
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87 int bestValley = secondPeak - 1;
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88 int bestValleyScore = -1;
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89 for (int i = secondPeak - 1; i > firstPeak; i--) {
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90 int fromFirst = (int) (biasTowardsWhite * (i - firstPeak));
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91 // Favor a "valley" that is not too close to either peak -- especially not the black peak --
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92 // and that has a low value of course
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93 int score = fromFirst * fromFirst * (secondPeak - i) * (256 - histogram[i]);
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94 if (score > bestValleyScore) {
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96 bestValleyScore = score;
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