2 * Copyright 2007 ZXing authors
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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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19 import com.google.zxing.BlackPointEstimationMethod;
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20 import com.google.zxing.MonochromeBitmapSource;
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21 import com.google.zxing.ReaderException;
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24 * <p>Encapsulates logic that estimates the optimal "black point", the luminance value
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25 * which is the best line between "white" and "black" in a grayscale image.</p>
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27 * <p>For an interesting discussion of this issue, see
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28 * <a href="http://webdiis.unizar.es/~neira/12082/thresholding.pdf">http://webdiis.unizar.es/~neira/12082/thresholding.pdf</a>.
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31 * NOTE: This class is not threadsafe.
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34 * @author dswitkin@google.com (Daniel Switkin)
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36 public final class BlackPointEstimator {
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38 private static final int LUMINANCE_BITS = 5;
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39 private static final int LUMINANCE_SHIFT = 8 - LUMINANCE_BITS;
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40 private static final int LUMINANCE_BUCKETS = 1 << LUMINANCE_BITS;
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42 private static int[] luminances = null;
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43 private static int[] histogram = null;
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45 private BlackPointEstimator() {
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48 private static void initArrays(int luminanceSize) {
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49 if (luminances == null || luminances.length < luminanceSize) {
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50 luminances = new int[luminanceSize];
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52 if (histogram == null) {
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53 histogram = new int[LUMINANCE_BUCKETS];
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55 for (int x = 0; x < LUMINANCE_BUCKETS; x++) {
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62 * Calculates the black point for the supplied bitmap.
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64 * @param source The bitmap to analyze.
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65 * @param method The pixel sampling technique to use.
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66 * @param argument The row index in the case of ROW_SAMPLING, otherwise ignored.
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67 * @return The black point as an integer 0-255.
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68 * @throws ReaderException An exception thrown if the blackpoint cannot be determined.
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70 public static int estimate(MonochromeBitmapSource source, BlackPointEstimationMethod method,
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71 int argument) throws ReaderException {
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72 int width = source.getWidth();
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73 int height = source.getHeight();
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76 if (method.equals(BlackPointEstimationMethod.TWO_D_SAMPLING)) {
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77 int minDimension = width < height ? width : height;
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78 int startX = (width - minDimension) >> 1;
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79 int startY = (height - minDimension) >> 1;
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80 for (int n = 0; n < minDimension; n++) {
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81 int luminance = source.getLuminance(startX + n, startY + n);
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82 histogram[luminance >> LUMINANCE_SHIFT]++;
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84 } else if (method.equals(BlackPointEstimationMethod.ROW_SAMPLING)) {
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85 if (argument < 0 || argument >= height) {
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86 throw new IllegalArgumentException("Row is not within the image: " + argument);
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89 luminances = source.getLuminanceRow(argument, luminances);
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90 for (int x = 0; x < width; x++) {
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91 histogram[luminances[x] >> LUMINANCE_SHIFT]++;
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94 throw new IllegalArgumentException("Unknown method");
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96 return findBestValley(histogram) << LUMINANCE_SHIFT;
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100 * <p>Given an array of <em>counts</em> of luminance values (i.e. a histogram), this method
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101 * decides which bucket of values corresponds to the black point -- which bucket contains the
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102 * count of the brightest luminance values that should be considered "black".</p>
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104 * @param buckets an array of <em>counts</em> of luminance values
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105 * @return index within argument of bucket corresponding to brightest values which should be
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106 * considered "black"
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107 * @throws ReaderException if "black" and "white" appear to be very close in luminance
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109 public static int findBestValley(int[] buckets) throws ReaderException {
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110 int numBuckets = buckets.length;
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111 int maxBucketCount = 0;
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112 // Find tallest peak in histogram
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114 int firstPeakSize = 0;
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115 for (int i = 0; i < numBuckets; i++) {
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116 if (buckets[i] > firstPeakSize) {
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118 firstPeakSize = buckets[i];
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120 if (buckets[i] > maxBucketCount) {
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121 maxBucketCount = buckets[i];
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125 // Find second-tallest peak -- well, another peak that is tall and not
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126 // so close to the first one
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127 int secondPeak = 0;
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128 int secondPeakScore = 0;
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129 for (int i = 0; i < numBuckets; i++) {
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130 int distanceToBiggest = i - firstPeak;
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131 // Encourage more distant second peaks by multiplying by square of distance
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132 int score = buckets[i] * distanceToBiggest * distanceToBiggest;
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133 if (score > secondPeakScore) {
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135 secondPeakScore = score;
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139 // Put firstPeak first
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140 if (firstPeak > secondPeak) {
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141 int temp = firstPeak;
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142 firstPeak = secondPeak;
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146 // Kind of arbitrary; if the two peaks are very close, then we figure there is so little
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147 // dynamic range in the image, that discriminating black and white is too error-prone.
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148 // Decoding the image/line is either pointless, or may in some cases lead to a false positive
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149 // for 1D formats, which are relatively lenient.
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150 // We arbitrarily say "close" is "<= 1/16 of the total histogram buckets apart"
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151 if (secondPeak - firstPeak <= numBuckets >> 4) {
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152 throw ReaderException.getInstance();
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155 // Find a valley between them that is low and closer to the white peak
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156 int bestValley = secondPeak - 1;
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157 int bestValleyScore = -1;
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158 for (int i = secondPeak - 1; i > firstPeak; i--) {
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159 int fromFirst = i - firstPeak;
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160 // Favor a "valley" that is not too close to either peak -- especially not the black peak --
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161 // and that has a low value of course
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162 int score = fromFirst * fromFirst * (secondPeak - i) * (maxBucketCount - buckets[i]);
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163 if (score > bestValleyScore) {
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165 bestValleyScore = score;
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