mirror of
https://github.com/zxing/zxing.git
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d4efd44fb0
git-svn-id: https://zxing.googlecode.com/svn/trunk@1202 59b500cc-1b3d-0410-9834-0bbf25fbcc57
574 lines
21 KiB
C#
Executable file
574 lines
21 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 BinaryBitmap = com.google.zxing.BinaryBitmap;
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using ReaderException = com.google.zxing.ReaderException;
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using ResultPoint = com.google.zxing.ResultPoint;
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using BitMatrix = com.google.zxing.common.BitMatrix;
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using DetectorResult = com.google.zxing.common.DetectorResult;
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using GridSampler = com.google.zxing.common.GridSampler;
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namespace com.google.zxing.pdf417.detector
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{
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/// <summary> <p>Encapsulates logic that can detect a PDF417 Code in an image, even if the
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/// PDF417 Code is rotated or skewed, or partially obscured.</p>
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///
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/// </summary>
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/// <author> SITA Lab (kevin.osullivan@sita.aero)
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/// </author>
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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 Detector
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{
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//UPGRADE_WARNING: Data types in Visual C# might be different. Verify the accuracy of narrowing conversions. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1042'"
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private static int MAX_AVG_VARIANCE = (int) SupportClass.Identity(((1 << 8) * 0.42f));
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//UPGRADE_WARNING: Data types in Visual C# might be different. Verify the accuracy of narrowing conversions. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1042'"
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private static int MAX_INDIVIDUAL_VARIANCE = (int) SupportClass.Identity(((1 << 8) * 0.8f));
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private const int SKEW_THRESHOLD = 2;
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// B S B S B S B S Bar/Space pattern
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// 11111111 0 1 0 1 0 1 000
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//UPGRADE_NOTE: Final was removed from the declaration of 'START_PATTERN'. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1003'"
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private static readonly int[] START_PATTERN = new int[]{8, 1, 1, 1, 1, 1, 1, 3};
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// 11111111 0 1 0 1 0 1 000
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//UPGRADE_NOTE: Final was removed from the declaration of 'START_PATTERN_REVERSE'. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1003'"
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private static readonly int[] START_PATTERN_REVERSE = new int[]{3, 1, 1, 1, 1, 1, 1, 8};
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// 1111111 0 1 000 1 0 1 00 1
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//UPGRADE_NOTE: Final was removed from the declaration of 'STOP_PATTERN'. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1003'"
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private static readonly int[] STOP_PATTERN = new int[]{7, 1, 1, 3, 1, 1, 1, 2, 1};
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// B S B S B S B S B Bar/Space pattern
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// 1111111 0 1 000 1 0 1 00 1
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//UPGRADE_NOTE: Final was removed from the declaration of 'STOP_PATTERN_REVERSE'. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1003'"
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private static readonly int[] STOP_PATTERN_REVERSE = new int[]{1, 2, 1, 1, 1, 3, 1, 1, 7};
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//UPGRADE_NOTE: Final was removed from the declaration of 'image '. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1003'"
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private BinaryBitmap image;
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public Detector(BinaryBitmap image)
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{
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this.image = image;
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}
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/// <summary> <p>Detects a PDF417 Code in an image, simply.</p>
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///
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/// </summary>
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/// <returns> {@link DetectorResult} encapsulating results of detecting a PDF417 Code
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/// </returns>
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/// <throws> ReaderException if no QR Code can be found </throws>
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public DetectorResult detect()
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{
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return detect(null);
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}
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/// <summary> <p>Detects a PDF417 Code in an image. Only checks 0 and 180 degree rotations.</p>
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///
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/// </summary>
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/// <param name="hints">optional hints to detector
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/// </param>
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/// <returns> {@link DetectorResult} encapsulating results of detecting a PDF417 Code
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/// </returns>
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/// <throws> ReaderException if no PDF417 Code can be found </throws>
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public DetectorResult detect(System.Collections.Hashtable hints)
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{
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// Fetch the 1 bit matrix once up front.
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BitMatrix matrix = image.BlackMatrix;
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// Try to find the vertices assuming the image is upright.
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ResultPoint[] vertices = findVertices(matrix);
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if (vertices == null)
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{
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// Maybe the image is rotated 180 degrees?
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vertices = findVertices180(matrix);
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if (vertices != null)
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{
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correctCodeWordVertices(vertices, true);
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}
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}
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else
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{
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correctCodeWordVertices(vertices, false);
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}
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if (vertices != null)
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{
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float moduleWidth = computeModuleWidth(vertices);
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if (moduleWidth < 1.0f)
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{
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throw ReaderException.Instance;
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}
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int dimension = computeDimension(vertices[4], vertices[6], vertices[5], vertices[7], moduleWidth);
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if (dimension < 1)
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{
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throw ReaderException.Instance;
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}
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// Deskew and sample image.
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BitMatrix bits = sampleGrid(matrix, vertices[4], vertices[5], vertices[6], vertices[7], dimension);
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return new DetectorResult(bits, new ResultPoint[]{vertices[4], vertices[5], vertices[6], vertices[7]});
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}
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else
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{
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throw ReaderException.Instance;
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}
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}
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/// <summary> Locate the vertices and the codewords area of a black blob using the Start
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/// and Stop patterns as locators. Assumes that the barcode begins in the left half
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/// of the image, and ends in the right half.
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/// TODO: Fix this assumption, allowing the barcode to be anywhere in the image.
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/// TODO: Scanning every row is very expensive. We should only do this for TRY_HARDER.
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///
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/// </summary>
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/// <param name="matrix">the scanned barcode image.
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/// </param>
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/// <returns> an array containing the vertices:
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/// vertices[0] x, y top left barcode
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/// vertices[1] x, y bottom left barcode
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/// vertices[2] x, y top right barcode
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/// vertices[3] x, y bottom right barcode
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/// vertices[4] x, y top left codeword area
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/// vertices[5] x, y bottom left codeword area
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/// vertices[6] x, y top right codeword area
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/// vertices[7] x, y bottom right codeword area
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/// </returns>
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private static ResultPoint[] findVertices(BitMatrix matrix)
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{
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int height = matrix.Height;
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int width = matrix.Width;
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int halfWidth = width >> 1;
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ResultPoint[] result = new ResultPoint[8];
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bool found = false;
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// Top Left
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for (int i = 0; i < height; i++)
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{
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int[] loc = findGuardPattern(matrix, 0, i, halfWidth, false, START_PATTERN);
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if (loc != null)
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{
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result[0] = new ResultPoint(loc[0], i);
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result[4] = new ResultPoint(loc[1], i);
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found = true;
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break;
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}
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}
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// Bottom left
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if (found)
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{
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// Found the Top Left vertex
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found = false;
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for (int i = height - 1; i > 0; i--)
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{
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int[] loc = findGuardPattern(matrix, 0, i, halfWidth, false, START_PATTERN);
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if (loc != null)
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{
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result[1] = new ResultPoint(loc[0], i);
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result[5] = new ResultPoint(loc[1], i);
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found = true;
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break;
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}
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}
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}
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// Top right
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if (found)
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{
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// Found the Bottom Left vertex
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found = false;
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for (int i = 0; i < height; i++)
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{
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int[] loc = findGuardPattern(matrix, halfWidth, i, halfWidth, false, STOP_PATTERN);
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if (loc != null)
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{
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result[2] = new ResultPoint(loc[1], i);
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result[6] = new ResultPoint(loc[0], i);
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found = true;
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break;
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}
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}
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}
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// Bottom right
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if (found)
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{
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// Found the Top right vertex
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found = false;
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for (int i = height - 1; i > 0; i--)
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{
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int[] loc = findGuardPattern(matrix, halfWidth, i, halfWidth, false, STOP_PATTERN);
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if (loc != null)
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{
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result[3] = new ResultPoint(loc[1], i);
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result[7] = new ResultPoint(loc[0], i);
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found = true;
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break;
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}
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}
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}
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return found?result:null;
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}
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/// <summary> Locate the vertices and the codewords area of a black blob using the Start
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/// and Stop patterns as locators. This assumes that the image is rotated 180
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/// degrees and if it locates the start and stop patterns at it will re-map
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/// the vertices for a 0 degree rotation.
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/// TODO: Change assumption about barcode location.
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/// TODO: Scanning every row is very expensive. We should only do this for TRY_HARDER.
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///
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/// </summary>
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/// <param name="matrix">the scanned barcode image.
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/// </param>
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/// <returns> an array containing the vertices:
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/// vertices[0] x, y top left barcode
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/// vertices[1] x, y bottom left barcode
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/// vertices[2] x, y top right barcode
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/// vertices[3] x, y bottom right barcode
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/// vertices[4] x, y top left codeword area
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/// vertices[5] x, y bottom left codeword area
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/// vertices[6] x, y top right codeword area
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/// vertices[7] x, y bottom right codeword area
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/// </returns>
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private static ResultPoint[] findVertices180(BitMatrix matrix)
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{
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int height = matrix.Height;
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int width = matrix.Width;
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int halfWidth = width >> 1;
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ResultPoint[] result = new ResultPoint[8];
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bool found = false;
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// Top Left
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for (int i = height - 1; i > 0; i--)
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{
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int[] loc = findGuardPattern(matrix, halfWidth, i, halfWidth, true, START_PATTERN_REVERSE);
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if (loc != null)
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{
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result[0] = new ResultPoint(loc[1], i);
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result[4] = new ResultPoint(loc[0], i);
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found = true;
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break;
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}
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}
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// Bottom Left
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if (found)
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{
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// Found the Top Left vertex
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found = false;
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for (int i = 0; i < height; i++)
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{
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int[] loc = findGuardPattern(matrix, halfWidth, i, halfWidth, true, START_PATTERN_REVERSE);
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if (loc != null)
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{
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result[1] = new ResultPoint(loc[1], i);
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result[5] = new ResultPoint(loc[0], i);
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found = true;
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break;
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}
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}
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}
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// Top Right
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if (found)
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{
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// Found the Bottom Left vertex
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found = false;
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for (int i = height - 1; i > 0; i--)
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{
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int[] loc = findGuardPattern(matrix, 0, i, halfWidth, false, STOP_PATTERN_REVERSE);
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if (loc != null)
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{
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result[2] = new ResultPoint(loc[0], i);
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result[6] = new ResultPoint(loc[1], i);
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found = true;
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break;
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}
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}
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}
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// Bottom Right
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if (found)
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{
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// Found the Top Right vertex
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found = false;
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for (int i = 0; i < height; i++)
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{
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int[] loc = findGuardPattern(matrix, 0, i, halfWidth, false, STOP_PATTERN_REVERSE);
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if (loc != null)
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{
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result[3] = new ResultPoint(loc[0], i);
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result[7] = new ResultPoint(loc[1], i);
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found = true;
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break;
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}
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}
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}
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return found?result:null;
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}
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/// <summary> Because we scan horizontally to detect the start and stop patterns, the vertical component of
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/// the codeword coordinates will be slightly wrong if there is any skew or rotation in the image.
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/// This method moves those points back onto the edges of the theoretically perfect bounding
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/// quadrilateral if needed.
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///
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/// </summary>
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/// <param name="vertices">The eight vertices located by findVertices().
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/// </param>
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private static void correctCodeWordVertices(ResultPoint[] vertices, bool upsideDown)
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{
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float skew = vertices[4].Y - vertices[6].Y;
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if (upsideDown)
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{
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skew = - skew;
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}
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if (skew > SKEW_THRESHOLD)
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{
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// Fix v4
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float length = vertices[4].X - vertices[0].X;
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float deltax = vertices[6].X - vertices[0].X;
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float deltay = vertices[6].Y - vertices[0].Y;
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float correction = length * deltay / deltax;
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vertices[4] = new ResultPoint(vertices[4].X, vertices[4].Y + correction);
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}
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else if (- skew > SKEW_THRESHOLD)
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{
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// Fix v6
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float length = vertices[2].X - vertices[6].X;
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float deltax = vertices[2].X - vertices[4].X;
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float deltay = vertices[2].Y - vertices[4].Y;
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float correction = length * deltay / deltax;
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vertices[6] = new ResultPoint(vertices[6].X, vertices[6].Y - correction);
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}
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skew = vertices[7].Y - vertices[5].Y;
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if (upsideDown)
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{
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skew = - skew;
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}
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if (skew > SKEW_THRESHOLD)
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{
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// Fix v5
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float length = vertices[5].X - vertices[1].X;
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float deltax = vertices[7].X - vertices[1].X;
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float deltay = vertices[7].Y - vertices[1].Y;
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float correction = length * deltay / deltax;
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vertices[5] = new ResultPoint(vertices[5].X, vertices[5].Y + correction);
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}
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else if (- skew > SKEW_THRESHOLD)
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{
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// Fix v7
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float length = vertices[3].X - vertices[7].X;
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float deltax = vertices[3].X - vertices[5].X;
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float deltay = vertices[3].Y - vertices[5].Y;
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float correction = length * deltay / deltax;
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vertices[7] = new ResultPoint(vertices[7].X, vertices[7].Y - correction);
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}
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}
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/// <summary> <p>Estimates module size (pixels in a module) based on the Start and End
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/// finder patterns.</p>
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///
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/// </summary>
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/// <param name="vertices">an array of vertices:
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/// vertices[0] x, y top left barcode
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/// vertices[1] x, y bottom left barcode
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/// vertices[2] x, y top right barcode
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/// vertices[3] x, y bottom right barcode
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/// vertices[4] x, y top left codeword area
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/// vertices[5] x, y bottom left codeword area
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/// vertices[6] x, y top right codeword area
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/// vertices[7] x, y bottom right codeword area
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/// </param>
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/// <returns> the module size.
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/// </returns>
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private static float computeModuleWidth(ResultPoint[] vertices)
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{
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float pixels1 = ResultPoint.distance(vertices[0], vertices[4]);
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float pixels2 = ResultPoint.distance(vertices[1], vertices[5]);
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float moduleWidth1 = (pixels1 + pixels2) / (17 * 2.0f);
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float pixels3 = ResultPoint.distance(vertices[6], vertices[2]);
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float pixels4 = ResultPoint.distance(vertices[7], vertices[3]);
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float moduleWidth2 = (pixels3 + pixels4) / (18 * 2.0f);
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return (moduleWidth1 + moduleWidth2) / 2.0f;
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}
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/// <summary> Computes the dimension (number of modules in a row) of the PDF417 Code
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/// based on vertices of the codeword area and estimated module size.
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///
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/// </summary>
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/// <param name="topLeft"> of codeword area
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/// </param>
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/// <param name="topRight"> of codeword area
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/// </param>
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/// <param name="bottomLeft"> of codeword area
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/// </param>
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/// <param name="bottomRight">of codeword are
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/// </param>
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/// <param name="moduleWidth">estimated module size
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/// </param>
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/// <returns> the number of modules in a row.
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/// </returns>
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private static int computeDimension(ResultPoint topLeft, ResultPoint topRight, ResultPoint bottomLeft, ResultPoint bottomRight, float moduleWidth)
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{
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int topRowDimension = round(ResultPoint.distance(topLeft, topRight) / moduleWidth);
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int bottomRowDimension = round(ResultPoint.distance(bottomLeft, bottomRight) / moduleWidth);
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return ((((topRowDimension + bottomRowDimension) >> 1) + 8) / 17) * 17;
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/*
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* int topRowDimension = round(ResultPoint.distance(topLeft,
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* topRight)); //moduleWidth); int bottomRowDimension =
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* round(ResultPoint.distance(bottomLeft, bottomRight)); //
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* moduleWidth); int dimension = ((topRowDimension + bottomRowDimension)
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* >> 1); // Round up to nearest 17 modules i.e. there are 17 modules per
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* codeword //int dimension = ((((topRowDimension + bottomRowDimension) >>
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* 1) + 8) / 17) * 17; return dimension;
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*/
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}
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private static BitMatrix sampleGrid(BitMatrix matrix, ResultPoint topLeft, ResultPoint bottomLeft, ResultPoint topRight, ResultPoint bottomRight, int dimension)
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{
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// Note that unlike the QR Code sampler, we didn't find the center of modules, but the
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// very corners. So there is no 0.5f here; 0.0f is right.
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GridSampler sampler = GridSampler.Instance;
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return sampler.sampleGrid(matrix, dimension, 0.0f, 0.0f, dimension, 0.0f, dimension, dimension, 0.0f, dimension, topLeft.X, topLeft.Y, topRight.X, topRight.Y, bottomRight.X, bottomRight.Y, bottomLeft.X, bottomLeft.Y); // p4FromY
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}
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/// <summary> Ends up being a bit faster than Math.round(). This merely rounds its
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/// argument to the nearest int, where x.5 rounds up.
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/// </summary>
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private static int round(float d)
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{
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//UPGRADE_WARNING: Data types in Visual C# might be different. Verify the accuracy of narrowing conversions. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1042'"
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return (int) (d + 0.5f);
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|
}
|
|
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/// <param name="matrix">row of black/white values to search
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/// </param>
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/// <param name="column">x position to start search
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/// </param>
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/// <param name="row">y position to start search
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/// </param>
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/// <param name="width">the number of pixels to search on this row
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/// </param>
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|
/// <param name="pattern">pattern of counts of number of black and white pixels that are
|
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/// being searched for as a pattern
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/// </param>
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/// <returns> start/end horizontal offset of guard pattern, as an array of two ints.
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|
/// </returns>
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|
private static int[] findGuardPattern(BitMatrix matrix, int column, int row, int width, bool whiteFirst, int[] pattern)
|
|
{
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|
int patternLength = pattern.Length;
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|
// TODO: Find a way to cache this array, as this method is called hundreds of times
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|
// per image, and we want to allocate as seldom as possible.
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|
int[] counters = new int[patternLength];
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|
bool isWhite = whiteFirst;
|
|
|
|
int counterPosition = 0;
|
|
int patternStart = column;
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|
for (int x = column; x < column + width; x++)
|
|
{
|
|
bool pixel = matrix.get_Renamed(x, row);
|
|
if (pixel ^ isWhite)
|
|
{
|
|
counters[counterPosition]++;
|
|
}
|
|
else
|
|
{
|
|
if (counterPosition == patternLength - 1)
|
|
{
|
|
if (patternMatchVariance(counters, pattern, MAX_INDIVIDUAL_VARIANCE) < MAX_AVG_VARIANCE)
|
|
{
|
|
return new int[]{patternStart, x};
|
|
}
|
|
patternStart += counters[0] + counters[1];
|
|
for (int y = 2; y < patternLength; y++)
|
|
{
|
|
counters[y - 2] = counters[y];
|
|
}
|
|
counters[patternLength - 2] = 0;
|
|
counters[patternLength - 1] = 0;
|
|
counterPosition--;
|
|
}
|
|
else
|
|
{
|
|
counterPosition++;
|
|
}
|
|
counters[counterPosition] = 1;
|
|
isWhite = !isWhite;
|
|
}
|
|
}
|
|
return null;
|
|
}
|
|
|
|
/// <summary> Determines how closely a set of observed counts of runs of black/white
|
|
/// values matches a given target pattern. This is reported as the ratio of
|
|
/// the total variance from the expected pattern proportions across all
|
|
/// pattern elements, to the length of the pattern.
|
|
///
|
|
/// </summary>
|
|
/// <param name="counters">observed counters
|
|
/// </param>
|
|
/// <param name="pattern">expected pattern
|
|
/// </param>
|
|
/// <param name="maxIndividualVariance">The most any counter can differ before we give up
|
|
/// </param>
|
|
/// <returns> ratio of total variance between counters and pattern compared to
|
|
/// total pattern size, where the ratio has been multiplied by 256.
|
|
/// So, 0 means no variance (perfect match); 256 means the total
|
|
/// variance between counters and patterns equals the pattern length,
|
|
/// higher values mean even more variance
|
|
/// </returns>
|
|
private static int patternMatchVariance(int[] counters, int[] pattern, int maxIndividualVariance)
|
|
{
|
|
int numCounters = counters.Length;
|
|
int total = 0;
|
|
int patternLength = 0;
|
|
for (int i = 0; i < numCounters; i++)
|
|
{
|
|
total += counters[i];
|
|
patternLength += pattern[i];
|
|
}
|
|
if (total < patternLength)
|
|
{
|
|
// If we don't even have one pixel per unit of bar width, assume this
|
|
// is too small to reliably match, so fail:
|
|
return System.Int32.MaxValue;
|
|
}
|
|
// We're going to fake floating-point math in integers. We just need to use more bits.
|
|
// Scale up patternLength so that intermediate values below like scaledCounter will have
|
|
// more "significant digits".
|
|
int unitBarWidth = (total << 8) / patternLength;
|
|
maxIndividualVariance = (maxIndividualVariance * unitBarWidth) >> 8;
|
|
|
|
int totalVariance = 0;
|
|
for (int x = 0; x < numCounters; x++)
|
|
{
|
|
int counter = counters[x] << 8;
|
|
int scaledPattern = pattern[x] * unitBarWidth;
|
|
int variance = counter > scaledPattern?counter - scaledPattern:scaledPattern - counter;
|
|
if (variance > maxIndividualVariance)
|
|
{
|
|
return System.Int32.MaxValue;
|
|
}
|
|
totalVariance += variance;
|
|
}
|
|
return totalVariance / total;
|
|
}
|
|
}
|
|
} |