zxing/csharp/pdf417/detector/Detector.cs

/*
* 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.
*/
using System;
using BinaryBitmap = com.google.zxing.BinaryBitmap;
using ReaderException = com.google.zxing.ReaderException;
using ResultPoint = com.google.zxing.ResultPoint;
using BitMatrix = com.google.zxing.common.BitMatrix;
using DetectorResult = com.google.zxing.common.DetectorResult;
using GridSampler = com.google.zxing.common.GridSampler;
namespace com.google.zxing.pdf417.detector
{
	
	/// <summary> <p>Encapsulates logic that can detect a PDF417 Code in an image, even if the
	/// PDF417 Code is rotated or skewed, or partially obscured.</p>
	/// 
	/// </summary>
	/// <author>  SITA Lab (kevin.osullivan@sita.aero)
	/// </author>
	/// <author>  dswitkin@google.com (Daniel Switkin)
	/// </author>
	/// <author>www.Redivivus.in (suraj.supekar@redivivus.in) - Ported from ZXING Java Source 
	/// </author>
	public sealed class Detector
	{
		
		//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'"
		private static int MAX_AVG_VARIANCE = (int) SupportClass.Identity(((1 << 8) * 0.42f));
		//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'"
		private static int MAX_INDIVIDUAL_VARIANCE = (int) SupportClass.Identity(((1 << 8) * 0.8f));
		private const int SKEW_THRESHOLD = 2;
		
		// B S B S B S B S Bar/Space pattern
		// 11111111 0 1 0 1 0 1 000
		//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'"
		private static readonly int[] START_PATTERN = new int[]{8, 1, 1, 1, 1, 1, 1, 3};
		
		// 11111111 0 1 0 1 0 1 000
		//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'"
		private static readonly int[] START_PATTERN_REVERSE = new int[]{3, 1, 1, 1, 1, 1, 1, 8};
		
		// 1111111 0 1 000 1 0 1 00 1
		//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'"
		private static readonly int[] STOP_PATTERN = new int[]{7, 1, 1, 3, 1, 1, 1, 2, 1};
		
		// B S B S B S B S B Bar/Space pattern
		// 1111111 0 1 000 1 0 1 00 1
		//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'"
		private static readonly int[] STOP_PATTERN_REVERSE = new int[]{1, 2, 1, 1, 1, 3, 1, 1, 7};
		
		//UPGRADE_NOTE: Final was removed from the declaration of 'image '. "ms-help://MS.VSCC.v80/dv_commoner/local/redirect.htm?index='!DefaultContextWindowIndex'&keyword='jlca1003'"
		private BinaryBitmap image;
		
		public Detector(BinaryBitmap image)
		{
			this.image = image;
		}
		
		/// <summary> <p>Detects a PDF417 Code in an image, simply.</p>
		/// 
		/// </summary>
		/// <returns> {@link DetectorResult} encapsulating results of detecting a PDF417 Code
		/// </returns>
		/// <throws>  ReaderException if no QR Code can be found </throws>
		public DetectorResult detect()
		{
			return detect(null);
		}
		
		/// <summary> <p>Detects a PDF417 Code in an image. Only checks 0 and 180 degree rotations.</p>
		/// 
		/// </summary>
		/// <param name="hints">optional hints to detector
		/// </param>
		/// <returns> {@link DetectorResult} encapsulating results of detecting a PDF417 Code
		/// </returns>
		/// <throws>  ReaderException if no PDF417 Code can be found </throws>
		public DetectorResult detect(System.Collections.Hashtable hints)
		{
			// Fetch the 1 bit matrix once up front.
			BitMatrix matrix = image.BlackMatrix;
			
			// Try to find the vertices assuming the image is upright.
			ResultPoint[] vertices = findVertices(matrix);
			if (vertices == null)
			{
				// Maybe the image is rotated 180 degrees?
				vertices = findVertices180(matrix);
				if (vertices != null)
				{
					correctCodeWordVertices(vertices, true);
				}
			}
			else
			{
				correctCodeWordVertices(vertices, false);
			}
			
			if (vertices != null)
			{
				float moduleWidth = computeModuleWidth(vertices);
				if (moduleWidth < 1.0f)
				{
					throw ReaderException.Instance;
				}
				
				int dimension = computeDimension(vertices[4], vertices[6], vertices[5], vertices[7], moduleWidth);
				if (dimension < 1)
				{
					throw ReaderException.Instance;
				}
				
				// Deskew and sample image.
				BitMatrix bits = sampleGrid(matrix, vertices[4], vertices[5], vertices[6], vertices[7], dimension);
				return new DetectorResult(bits, new ResultPoint[]{vertices[4], vertices[5], vertices[6], vertices[7]});
			}
			else
			{
				throw ReaderException.Instance;
			}
		}
		
		/// <summary> Locate the vertices and the codewords area of a black blob using the Start
		/// and Stop patterns as locators. Assumes that the barcode begins in the left half
		/// of the image, and ends in the right half.
		/// TODO: Fix this assumption, allowing the barcode to be anywhere in the image.
		/// TODO: Scanning every row is very expensive. We should only do this for TRY_HARDER.
		/// 
		/// </summary>
		/// <param name="matrix">the scanned barcode image.
		/// </param>
		/// <returns> an array containing the vertices:
		/// vertices[0] x, y top left barcode
		/// vertices[1] x, y bottom left barcode
		/// vertices[2] x, y top right barcode
		/// vertices[3] x, y bottom right barcode
		/// vertices[4] x, y top left codeword area
		/// vertices[5] x, y bottom left codeword area
		/// vertices[6] x, y top right codeword area
		/// vertices[7] x, y bottom right codeword area
		/// </returns>
		private static ResultPoint[] findVertices(BitMatrix matrix)
		{
			int height = matrix.Height;
			int width = matrix.Width;
			int halfWidth = width >> 1;
			
			ResultPoint[] result = new ResultPoint[8];
			bool found = false;
			
			// Top Left
			for (int i = 0; i < height; i++)
			{
				int[] loc = findGuardPattern(matrix, 0, i, halfWidth, false, START_PATTERN);
				if (loc != null)
				{
					result[0] = new ResultPoint(loc[0], i);
					result[4] = new ResultPoint(loc[1], i);
					found = true;
					break;
				}
			}
			// Bottom left
			if (found)
			{
				// Found the Top Left vertex
				found = false;
				for (int i = height - 1; i > 0; i--)
				{
					int[] loc = findGuardPattern(matrix, 0, i, halfWidth, false, START_PATTERN);
					if (loc != null)
					{
						result[1] = new ResultPoint(loc[0], i);
						result[5] = new ResultPoint(loc[1], i);
						found = true;
						break;
					}
				}
			}
			// Top right
			if (found)
			{
				// Found the Bottom Left vertex
				found = false;
				for (int i = 0; i < height; i++)
				{
					int[] loc = findGuardPattern(matrix, halfWidth, i, halfWidth, false, STOP_PATTERN);
					if (loc != null)
					{
						result[2] = new ResultPoint(loc[1], i);
						result[6] = new ResultPoint(loc[0], i);
						found = true;
						break;
					}
				}
			}
			// Bottom right
			if (found)
			{
				// Found the Top right vertex
				found = false;
				for (int i = height - 1; i > 0; i--)
				{
					int[] loc = findGuardPattern(matrix, halfWidth, i, halfWidth, false, STOP_PATTERN);
					if (loc != null)
					{
						result[3] = new ResultPoint(loc[1], i);
						result[7] = new ResultPoint(loc[0], i);
						found = true;
						break;
					}
				}
			}
			return found?result:null;
		}
		
		/// <summary> Locate the vertices and the codewords area of a black blob using the Start
		/// and Stop patterns as locators. This assumes that the image is rotated 180
		/// degrees and if it locates the start and stop patterns at it will re-map
		/// the vertices for a 0 degree rotation.
		/// TODO: Change assumption about barcode location.
		/// TODO: Scanning every row is very expensive. We should only do this for TRY_HARDER.
		/// 
		/// </summary>
		/// <param name="matrix">the scanned barcode image.
		/// </param>
		/// <returns> an array containing the vertices:
		/// vertices[0] x, y top left barcode
		/// vertices[1] x, y bottom left barcode
		/// vertices[2] x, y top right barcode
		/// vertices[3] x, y bottom right barcode
		/// vertices[4] x, y top left codeword area
		/// vertices[5] x, y bottom left codeword area
		/// vertices[6] x, y top right codeword area
		/// vertices[7] x, y bottom right codeword area
		/// </returns>
		private static ResultPoint[] findVertices180(BitMatrix matrix)
		{
			int height = matrix.Height;
			int width = matrix.Width;
			int halfWidth = width >> 1;
			
			ResultPoint[] result = new ResultPoint[8];
			bool found = false;
			
			// Top Left
			for (int i = height - 1; i > 0; i--)
			{
				int[] loc = findGuardPattern(matrix, halfWidth, i, halfWidth, true, START_PATTERN_REVERSE);
				if (loc != null)
				{
					result[0] = new ResultPoint(loc[1], i);
					result[4] = new ResultPoint(loc[0], i);
					found = true;
					break;
				}
			}
			// Bottom Left
			if (found)
			{
				// Found the Top Left vertex
				found = false;
				for (int i = 0; i < height; i++)
				{
					int[] loc = findGuardPattern(matrix, halfWidth, i, halfWidth, true, START_PATTERN_REVERSE);
					if (loc != null)
					{
						result[1] = new ResultPoint(loc[1], i);
						result[5] = new ResultPoint(loc[0], i);
						found = true;
						break;
					}
				}
			}
			// Top Right
			if (found)
			{
				// Found the Bottom Left vertex
				found = false;
				for (int i = height - 1; i > 0; i--)
				{
					int[] loc = findGuardPattern(matrix, 0, i, halfWidth, false, STOP_PATTERN_REVERSE);
					if (loc != null)
					{
						result[2] = new ResultPoint(loc[0], i);
						result[6] = new ResultPoint(loc[1], i);
						found = true;
						break;
					}
				}
			}
			// Bottom Right
			if (found)
			{
				// Found the Top Right vertex
				found = false;
				for (int i = 0; i < height; i++)
				{
					int[] loc = findGuardPattern(matrix, 0, i, halfWidth, false, STOP_PATTERN_REVERSE);
					if (loc != null)
					{
						result[3] = new ResultPoint(loc[0], i);
						result[7] = new ResultPoint(loc[1], i);
						found = true;
						break;
					}
				}
			}
			return found?result:null;
		}
		
		/// <summary> Because we scan horizontally to detect the start and stop patterns, the vertical component of
		/// the codeword coordinates will be slightly wrong if there is any skew or rotation in the image.
		/// This method moves those points back onto the edges of the theoretically perfect bounding
		/// quadrilateral if needed.
		/// 
		/// </summary>
		/// <param name="vertices">The eight vertices located by findVertices().
		/// </param>
		private static void  correctCodeWordVertices(ResultPoint[] vertices, bool upsideDown)
		{
			float skew = vertices[4].Y - vertices[6].Y;
			if (upsideDown)
			{
				skew = - skew;
			}
			if (skew > SKEW_THRESHOLD)
			{
				// Fix v4
				float length = vertices[4].X - vertices[0].X;
				float deltax = vertices[6].X - vertices[0].X;
				float deltay = vertices[6].Y - vertices[0].Y;
				float correction = length * deltay / deltax;
				vertices[4] = new ResultPoint(vertices[4].X, vertices[4].Y + correction);
			}
			else if (- skew > SKEW_THRESHOLD)
			{
				// Fix v6
				float length = vertices[2].X - vertices[6].X;
				float deltax = vertices[2].X - vertices[4].X;
				float deltay = vertices[2].Y - vertices[4].Y;
				float correction = length * deltay / deltax;
				vertices[6] = new ResultPoint(vertices[6].X, vertices[6].Y - correction);
			}
			
			skew = vertices[7].Y - vertices[5].Y;
			if (upsideDown)
			{
				skew = - skew;
			}
			if (skew > SKEW_THRESHOLD)
			{
				// Fix v5
				float length = vertices[5].X - vertices[1].X;
				float deltax = vertices[7].X - vertices[1].X;
				float deltay = vertices[7].Y - vertices[1].Y;
				float correction = length * deltay / deltax;
				vertices[5] = new ResultPoint(vertices[5].X, vertices[5].Y + correction);
			}
			else if (- skew > SKEW_THRESHOLD)
			{
				// Fix v7
				float length = vertices[3].X - vertices[7].X;
				float deltax = vertices[3].X - vertices[5].X;
				float deltay = vertices[3].Y - vertices[5].Y;
				float correction = length * deltay / deltax;
				vertices[7] = new ResultPoint(vertices[7].X, vertices[7].Y - correction);
			}
		}
		
		/// <summary> <p>Estimates module size (pixels in a module) based on the Start and End
		/// finder patterns.</p>
		/// 
		/// </summary>
		/// <param name="vertices">an array of vertices:
		/// vertices[0] x, y top left barcode
		/// vertices[1] x, y bottom left barcode
		/// vertices[2] x, y top right barcode
		/// vertices[3] x, y bottom right barcode
		/// vertices[4] x, y top left codeword area
		/// vertices[5] x, y bottom left codeword area
		/// vertices[6] x, y top right codeword area
		/// vertices[7] x, y bottom right codeword area
		/// </param>
		/// <returns> the module size.
		/// </returns>
		private static float computeModuleWidth(ResultPoint[] vertices)
		{
			float pixels1 = ResultPoint.distance(vertices[0], vertices[4]);
			float pixels2 = ResultPoint.distance(vertices[1], vertices[5]);
			float moduleWidth1 = (pixels1 + pixels2) / (17 * 2.0f);
			float pixels3 = ResultPoint.distance(vertices[6], vertices[2]);
			float pixels4 = ResultPoint.distance(vertices[7], vertices[3]);
			float moduleWidth2 = (pixels3 + pixels4) / (18 * 2.0f);
			return (moduleWidth1 + moduleWidth2) / 2.0f;
		}
		
		/// <summary> Computes the dimension (number of modules in a row) of the PDF417 Code
		/// based on vertices of the codeword area and estimated module size.
		/// 
		/// </summary>
		/// <param name="topLeft">    of codeword area
		/// </param>
		/// <param name="topRight">   of codeword area
		/// </param>
		/// <param name="bottomLeft"> of codeword area
		/// </param>
		/// <param name="bottomRight">of codeword are
		/// </param>
		/// <param name="moduleWidth">estimated module size
		/// </param>
		/// <returns> the number of modules in a row.
		/// </returns>
		private static int computeDimension(ResultPoint topLeft, ResultPoint topRight, ResultPoint bottomLeft, ResultPoint bottomRight, float moduleWidth)
		{
			int topRowDimension = round(ResultPoint.distance(topLeft, topRight) / moduleWidth);
			int bottomRowDimension = round(ResultPoint.distance(bottomLeft, bottomRight) / moduleWidth);
			return ((((topRowDimension + bottomRowDimension) >> 1) + 8) / 17) * 17;
			/*
			* int topRowDimension = round(ResultPoint.distance(topLeft,
			* topRight)); //moduleWidth); int bottomRowDimension =
			* round(ResultPoint.distance(bottomLeft, bottomRight)); //
			* moduleWidth); int dimension = ((topRowDimension + bottomRowDimension)
			* >> 1); // Round up to nearest 17 modules i.e. there are 17 modules per
			* codeword //int dimension = ((((topRowDimension + bottomRowDimension) >>
			* 1) + 8) / 17) * 17; return dimension;
			*/
		}
		
		private static BitMatrix sampleGrid(BitMatrix matrix, ResultPoint topLeft, ResultPoint bottomLeft, ResultPoint topRight, ResultPoint bottomRight, int dimension)
		{
			
			// Note that unlike the QR Code sampler, we didn't find the center of modules, but the
			// very corners. So there is no 0.5f here; 0.0f is right.
			GridSampler sampler = GridSampler.Instance;
			
			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
		}
		
		/// <summary> Ends up being a bit faster than Math.round(). This merely rounds its
		/// argument to the nearest int, where x.5 rounds up.
		/// </summary>
		private static int round(float d)
		{
			//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'"
			return (int) (d + 0.5f);
		}
		
		/// <param name="matrix">row of black/white values to search
		/// </param>
		/// <param name="column">x position to start search
		/// </param>
		/// <param name="row">y position to start search
		/// </param>
		/// <param name="width">the number of pixels to search on this row
		/// </param>
		/// <param name="pattern">pattern of counts of number of black and white pixels that are
		/// being searched for as a pattern
		/// </param>
		/// <returns> start/end horizontal offset of guard pattern, as an array of two ints.
		/// </returns>
		private static int[] findGuardPattern(BitMatrix matrix, int column, int row, int width, bool whiteFirst, int[] pattern)
		{
			int patternLength = pattern.Length;
			// TODO: Find a way to cache this array, as this method is called hundreds of times
			// per image, and we want to allocate as seldom as possible.
			int[] counters = new int[patternLength];
			bool isWhite = whiteFirst;
			
			int counterPosition = 0;
			int patternStart = column;
			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;
		}
	}
}