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d4efd44fb0
git-svn-id: https://zxing.googlecode.com/svn/trunk@1202 59b500cc-1b3d-0410-9834-0bbf25fbcc57
187 lines
6.5 KiB
C#
Executable file
187 lines
6.5 KiB
C#
Executable file
/*
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* Copyright 2009 ZXing authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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using System;
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using Binarizer = com.google.zxing.Binarizer;
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using LuminanceSource = com.google.zxing.LuminanceSource;
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using ReaderException = com.google.zxing.ReaderException;
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namespace com.google.zxing.common
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{
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/// <summary> This class implements a local thresholding algorithm, which while slower than the
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/// GlobalHistogramBinarizer, is fairly efficient for what it does. It is designed for
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/// high frequency images of barcodes with black data on white backgrounds. For this application,
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/// it does a much better job than a global blackpoint with severe shadows and gradients.
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/// However it tends to produce artifacts on lower frequency images and is therefore not
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/// a good general purpose binarizer for uses outside ZXing.
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///
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/// This class extends GlobalHistogramBinarizer, using the older histogram approach for 1D readers,
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/// and the newer local approach for 2D readers. 1D decoding using a per-row histogram is already
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/// inherently local, and only fails for horizontal gradients. We can revisit that problem later,
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/// but for now it was not a win to use local blocks for 1D.
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///
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/// This Binarizer is the default for the unit tests and the recommended class for library users.
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///
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/// </summary>
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/// <author> dswitkin@google.com (Daniel Switkin)
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/// </author>
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/// <author>www.Redivivus.in (suraj.supekar@redivivus.in) - Ported from ZXING Java Source
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/// </author>
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public sealed class HybridBinarizer:GlobalHistogramBinarizer
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{
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override public BitMatrix BlackMatrix
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{
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get
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{
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binarizeEntireImage();
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return matrix;
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}
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}
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// This class uses 5x5 blocks to compute local luminance, where each block is 8x8 pixels.
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// So this is the smallest dimension in each axis we can accept.
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private const int MINIMUM_DIMENSION = 40;
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private BitMatrix matrix = null;
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public HybridBinarizer(LuminanceSource source):base(source)
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{
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}
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public override Binarizer createBinarizer(LuminanceSource source)
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{
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return new HybridBinarizer(source);
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}
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// Calculates the final BitMatrix once for all requests. This could be called once from the
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// constructor instead, but there are some advantages to doing it lazily, such as making
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// profiling easier, and not doing heavy lifting when callers don't expect it.
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private void binarizeEntireImage()
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{
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if (matrix == null)
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{
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LuminanceSource source = LuminanceSource;
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if (source.Width >= MINIMUM_DIMENSION && source.Height >= MINIMUM_DIMENSION)
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{
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sbyte[] luminances = source.Matrix;
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int width = source.Width;
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int height = source.Height;
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int subWidth = width >> 3;
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int subHeight = height >> 3;
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int[][] blackPoints = calculateBlackPoints(luminances, subWidth, subHeight, width);
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matrix = new BitMatrix(width, height);
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calculateThresholdForBlock(luminances, subWidth, subHeight, width, blackPoints, matrix);
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}
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else
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{
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// If the image is too small, fall back to the global histogram approach.
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matrix = base.BlackMatrix;
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}
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}
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}
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// For each 8x8 block in the image, calculate the average black point using a 5x5 grid
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// of the blocks around it. Also handles the corner cases, but will ignore up to 7 pixels
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// on the right edge and 7 pixels at the bottom of the image if the overall dimensions are not
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// multiples of eight. In practice, leaving those pixels white does not seem to be a problem.
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private static void calculateThresholdForBlock(sbyte[] luminances, int subWidth, int subHeight, int stride, int[][] blackPoints, BitMatrix matrix)
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{
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for (int y = 0; y < subHeight; y++)
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{
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for (int x = 0; x < subWidth; x++)
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{
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int left = (x > 1)?x:2;
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left = (left < subWidth - 2)?left:subWidth - 3;
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int top = (y > 1)?y:2;
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top = (top < subHeight - 2)?top:subHeight - 3;
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int sum = 0;
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for (int z = - 2; z <= 2; z++)
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{
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int[] blackRow = blackPoints[top + z];
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sum += blackRow[left - 2];
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sum += blackRow[left - 1];
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sum += blackRow[left];
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sum += blackRow[left + 1];
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sum += blackRow[left + 2];
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}
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int average = sum / 25;
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threshold8x8Block(luminances, x << 3, y << 3, average, stride, matrix);
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}
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}
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}
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// Applies a single threshold to an 8x8 block of pixels.
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private static void threshold8x8Block(sbyte[] luminances, int xoffset, int yoffset, int threshold, int stride, BitMatrix matrix)
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{
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for (int y = 0; y < 8; y++)
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{
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int offset = (yoffset + y) * stride + xoffset;
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for (int x = 0; x < 8; x++)
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{
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int pixel = luminances[offset + x] & 0xff;
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if (pixel < threshold)
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{
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matrix.set_Renamed(xoffset + x, yoffset + y);
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}
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}
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}
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}
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// Calculates a single black point for each 8x8 block of pixels and saves it away.
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private static int[][] calculateBlackPoints(sbyte[] luminances, int subWidth, int subHeight, int stride)
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{
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int[][] blackPoints = new int[subHeight][];
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for (int i = 0; i < subHeight; i++)
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{
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blackPoints[i] = new int[subWidth];
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}
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for (int y = 0; y < subHeight; y++)
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{
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for (int x = 0; x < subWidth; x++)
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{
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int sum = 0;
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int min = 255;
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int max = 0;
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for (int yy = 0; yy < 8; yy++)
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{
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int offset = ((y << 3) + yy) * stride + (x << 3);
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for (int xx = 0; xx < 8; xx++)
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{
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int pixel = luminances[offset + xx] & 0xff;
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sum += pixel;
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if (pixel < min)
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{
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min = pixel;
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}
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if (pixel > max)
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{
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max = pixel;
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}
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}
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}
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// If the contrast is inadequate, use half the minimum, so that this block will be
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// treated as part of the white background, but won't drag down neighboring blocks
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// too much.
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int average = (max - min > 24)?(sum >> 6):(min >> 1);
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blackPoints[y][x] = average;
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}
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}
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return blackPoints;
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}
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}
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} |