content: /*
   * 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.ailiwean.core.zxing.core.common;
  
  
  import com.ailiwean.core.zxing.core.Binarizer;
  import com.ailiwean.core.zxing.core.LuminanceSource;
  import com.ailiwean.core.zxing.core.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.
   * <p>
   * 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 static final byte[] EMPTY = new byte[0];
  
      private byte[] luminances;
      private final int[] buckets;
      protected BitMatrix bitMatrix;
  
      public GlobalHistogramBinarizer(LuminanceSource source) {
          super(source);
          luminances = EMPTY;
          buckets = new int[LUMINANCE_BUCKETS];
      }
  
      // Applies simple sharpening to the row data to improve performance of the 1D Readers.
      @Override
      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++) {
              localBuckets[(localLuminances[x] & 0xff) >> LUMINANCE_SHIFT]++;
          }
          int blackPoint = estimateBlackPoint(localBuckets);
  
          if (width < 3) {
              // Special case for very small images
              for (int x = 0; x < width; x++) {
                  if ((localLuminances[x] & 0xff) < blackPoint) {
                      row.set(x);
                  }
              }
          } else {
              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.
                  if (((center * 4) - left - right) / 2 < 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.
      @Override
      public BitMatrix getBlackMatrix() throws NotFoundException {
          if (bitMatrix == null) {
              synchronized (this) {
                  if (bitMatrix == null)
                      bitMatrix = creatBitMatrix();
              }
          }
          return bitMatrix;
      }
  
  
      protected BitMatrix creatBitMatrix() throws NotFoundException {
          LuminanceSource source = getLuminanceSource();
          int width = source.getWidth();
          int height = source.getHeight();
          bitMatrix = 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 * 4) / 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) {
                      bitMatrix.set(x, y);
                  }
              }
          }
          return bitMatrix;
      }
  
      @Override
      public Binarizer createBinarizer(LuminanceSource source) {
          return new GlobalHistogramBinarizer(source);
      }
  
      private void initArrays(int luminanceSize) {
          if (luminances.length < luminanceSize) {
              luminances = new byte[luminanceSize];
          }
          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 / 16) {
              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;
      }
  
  }
  