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diff --git a/libraries/zxing/src/com/google/zxing/common/GlobalHistogramBinarizer.java b/libraries/zxing/src/com/google/zxing/common/GlobalHistogramBinarizer.java
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+++ b/libraries/zxing/src/com/google/zxing/common/GlobalHistogramBinarizer.java
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+/*
+ * Copyright 2009 ZXing authors
+ *
+ * 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 com.google.zxing.common;
+
+import com.google.zxing.Binarizer;
+import com.google.zxing.LuminanceSource;
+import com.google.zxing.NotFoundException;
+
+/**
+ * This Binarizer implementation uses the old ZXing global histogram approach. It is suitable
+ * for low-end mobile devices which don't have enough CPU or memory to use a local thresholding
+ * algorithm. However, because it picks a global black point, it cannot handle difficult shadows
+ * and gradients.
+ *
+ * Faster mobile devices and all desktop applications should probably use HybridBinarizer instead.
+ *
+ * @author dswitkin@google.com (Daniel Switkin)
+ * @author Sean Owen
+ */
+public class GlobalHistogramBinarizer extends Binarizer {
+
+  private static final int LUMINANCE_BITS = 5;
+  private static final int LUMINANCE_SHIFT = 8 - LUMINANCE_BITS;
+  private static final int LUMINANCE_BUCKETS = 1 << LUMINANCE_BITS;
+
+  private byte[] luminances = null;
+  private int[] buckets = null;
+
+  public GlobalHistogramBinarizer(LuminanceSource source) {
+    super(source);
+  }
+
+  // Applies simple sharpening to the row data to improve performance of the 1D Readers.
+  public BitArray getBlackRow(int y, BitArray row) throws NotFoundException {
+    LuminanceSource source = getLuminanceSource();
+    int width = source.getWidth();
+    if (row == null || row.getSize() < width) {
+      row = new BitArray(width);
+    } else {
+      row.clear();
+    }
+
+    initArrays(width);
+    byte[] localLuminances = source.getRow(y, luminances);
+    int[] localBuckets = buckets;
+    for (int x = 0; x < width; x++) {
+      int pixel = localLuminances[x] & 0xff;
+      localBuckets[pixel >> LUMINANCE_SHIFT]++;
+    }
+    int blackPoint = estimateBlackPoint(localBuckets);
+
+    int left = localLuminances[0] & 0xff;
+    int center = localLuminances[1] & 0xff;
+    for (int x = 1; x < width - 1; x++) {
+      int right = localLuminances[x + 1] & 0xff;
+      // A simple -1 4 -1 box filter with a weight of 2.
+      int luminance = ((center << 2) - left - right) >> 1;
+      if (luminance < blackPoint) {
+        row.set(x);
+      }
+      left = center;
+      center = right;
+    }
+    return row;
+  }
+
+  // Does not sharpen the data, as this call is intended to only be used by 2D Readers.
+  public BitMatrix getBlackMatrix() throws NotFoundException {
+    LuminanceSource source = getLuminanceSource();
+    int width = source.getWidth();
+    int height = source.getHeight();
+    BitMatrix matrix = new BitMatrix(width, height);
+
+    // Quickly calculates the histogram by sampling four rows from the image. This proved to be
+    // more robust on the blackbox tests than sampling a diagonal as we used to do.
+    initArrays(width);
+    int[] localBuckets = buckets;
+    for (int y = 1; y < 5; y++) {
+      int row = height * y / 5;
+      byte[] localLuminances = source.getRow(row, luminances);
+      int right = (width << 2) / 5;
+      for (int x = width / 5; x < right; x++) {
+        int pixel = localLuminances[x] & 0xff;
+        localBuckets[pixel >> LUMINANCE_SHIFT]++;
+      }
+    }
+    int blackPoint = estimateBlackPoint(localBuckets);
+
+    // We delay reading the entire image luminance until the black point estimation succeeds.
+    // Although we end up reading four rows twice, it is consistent with our motto of
+    // "fail quickly" which is necessary for continuous scanning.
+    byte[] localLuminances = source.getMatrix();
+    for (int y = 0; y < height; y++) {
+      int offset = y * width;
+      for (int x = 0; x< width; x++) {
+        int pixel = localLuminances[offset + x] & 0xff;
+        if (pixel < blackPoint) {
+          matrix.set(x, y);
+        }
+      }
+    }
+
+    return matrix;
+  }
+
+  public Binarizer createBinarizer(LuminanceSource source) {
+    return new GlobalHistogramBinarizer(source);
+  }
+
+  private void initArrays(int luminanceSize) {
+    if (luminances == null || luminances.length < luminanceSize) {
+      luminances = new byte[luminanceSize];
+    }
+    if (buckets == null) {
+      buckets = new int[LUMINANCE_BUCKETS];
+    } else {
+      for (int x = 0; x < LUMINANCE_BUCKETS; x++) {
+        buckets[x] = 0;
+      }
+    }
+  }
+
+  private static int estimateBlackPoint(int[] buckets) throws NotFoundException {
+    // Find the tallest peak in the histogram.
+    int numBuckets = buckets.length;
+    int maxBucketCount = 0;
+    int firstPeak = 0;
+    int firstPeakSize = 0;
+    for (int x = 0; x < numBuckets; x++) {
+      if (buckets[x] > firstPeakSize) {
+        firstPeak = x;
+        firstPeakSize = buckets[x];
+      }
+      if (buckets[x] > maxBucketCount) {
+        maxBucketCount = buckets[x];
+      }
+    }
+
+    // Find the second-tallest peak which is somewhat far from the tallest peak.
+    int secondPeak = 0;
+    int secondPeakScore = 0;
+    for (int x = 0; x < numBuckets; x++) {
+      int distanceToBiggest = x - firstPeak;
+      // Encourage more distant second peaks by multiplying by square of distance.
+      int score = buckets[x] * distanceToBiggest * distanceToBiggest;
+      if (score > secondPeakScore) {
+        secondPeak = x;
+        secondPeakScore = score;
+      }
+    }
+
+    // Make sure firstPeak corresponds to the black peak.
+    if (firstPeak > secondPeak) {
+      int temp = firstPeak;
+      firstPeak = secondPeak;
+      secondPeak = temp;
+    }
+
+    // If there is too little contrast in the image to pick a meaningful black point, throw rather
+    // than waste time trying to decode the image, and risk false positives.
+    if (secondPeak - firstPeak <= numBuckets >> 4) {
+      throw NotFoundException.getNotFoundInstance();
+    }
+
+    // Find a valley between them that is low and closer to the white peak.
+    int bestValley = secondPeak - 1;
+    int bestValleyScore = -1;
+    for (int x = secondPeak - 1; x > firstPeak; x--) {
+      int fromFirst = x - firstPeak;
+      int score = fromFirst * fromFirst * (secondPeak - x) * (maxBucketCount - buckets[x]);
+      if (score > bestValleyScore) {
+        bestValley = x;
+        bestValleyScore = score;
+      }
+    }
+
+    return bestValley << LUMINANCE_SHIFT;
+  }
+
+}