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Document Layout Analysis - IPageSegmenter, Docstrum
- Create a TextBlock class - Creates IPageSegmenter - Add other useful distances: angle, etc. - Update RecursiveXYCut - With IPageSegmenter and TextBlock - Make XYNode and XYLeaf internal - Optimise (faster) NearestNeighbourWordExtractor and isolate the clustering algorithms for use outside of this class - Implement a Docstrum inspired page segmentation algorithm
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BobLd
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src/UglyToad.PdfPig/DocumentLayoutAnalysis/DocstrumBB.cs
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src/UglyToad.PdfPig/DocumentLayoutAnalysis/DocstrumBB.cs
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using System;
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using System.Collections.Concurrent;
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using System.Collections.Generic;
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using System.Linq;
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using System.Threading.Tasks;
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using UglyToad.PdfPig.Content;
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using UglyToad.PdfPig.Geometry;
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namespace UglyToad.PdfPig.DocumentLayoutAnalysis
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{
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/// <summary>
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/// The Docstrum algorithm is a bottom-up page segmentation technique based on nearest-neighborhood
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/// clustering of connected components extracted from the document.
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/// This implementation leverages bounding boxes and does not exactly replicates the original algorithm.
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/// <para>See 'The document spectrum for page layout analysis.' by L. O’Gorman.</para>
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/// </summary>
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public class DocstrumBB : IPageSegmenter
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{
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/// <summary>
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/// Create an instance of Docstrum for bounding boxes page segmenter, <see cref="DocstrumBB"/>.
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/// </summary>
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public static DocstrumBB Instance { get; } = new DocstrumBB();
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/// <summary>
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/// Get the blocks.
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/// <para>Uses wlAngleLB = -30, wlAngleUB = 30, blAngleLB = -135, blAngleUB = -45, blMulti = 1.3.</para>
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/// </summary>
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/// <param name="pageWords"></param>
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/// <returns></returns>
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public IReadOnlyList<TextBlock> GetBlocks(IEnumerable<Word> pageWords)
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{
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return GetBlocks(pageWords, -30, 30, -135, -45, 1.3);
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}
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/// <summary>
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/// Get the blocks. See original paper for more information.
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/// </summary>
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/// <param name="pageWords"></param>
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/// <param name="wlAngleLB">Within-line lower bound angle.</param>
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/// <param name="wlAngleUB">Within-line upper bound angle.</param>
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/// <param name="blAngleLB">Between-line lower bound angle.</param>
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/// <param name="blAngleUB">Between-line upper bound angle.</param>
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/// <param name="blMultiplier">Multiplier that gives the maximum perpendicular distance between
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/// text lines for blocking. Maximum distance will be this number times the between-line
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/// distance found by the analysis.</param>
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/// <returns></returns>
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public IReadOnlyList<TextBlock> GetBlocks(IEnumerable<Word> pageWords, double wlAngleLB, double wlAngleUB,
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double blAngleLB, double blAngleUB, double blMultiplier)
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{
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var pageWordsArr = pageWords.Where(w => !string.IsNullOrWhiteSpace(w.Text)).ToArray(); // remove white spaces
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var withinLineDistList = new ConcurrentBag<double[]>();
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var betweenLineDistList = new ConcurrentBag<double[]>();
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// 1. Estimate in line and between line spacing
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Parallel.For(0, pageWordsArr.Length, i =>
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{
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var word = pageWordsArr[i];
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// Within-line distance
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var pointWL = GetNearestPointData(pageWordsArr, word,
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bb => bb.BottomRight, bb => bb.BottomRight,
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bb => bb.BottomLeft, bb => bb.BottomLeft,
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wlAngleLB, wlAngleUB, Distances.Horizontal);
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if (pointWL != null) withinLineDistList.Add(pointWL);
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// Between-line distance
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var pointBL = GetNearestPointData(pageWordsArr, word,
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bb => bb.BottomLeft, bb => bb.Centroid,
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bb => bb.TopLeft, bb => bb.Centroid,
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blAngleLB, blAngleUB, Distances.Vertical);
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if (pointBL != null) betweenLineDistList.Add(pointBL);
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});
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double withinLineDistance = GetPeakAverageDistance(withinLineDistList);
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double betweenLineDistance = GetPeakAverageDistance(betweenLineDistList);
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// 2. Find lines of text
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double maxDistWL = Math.Min(3 * withinLineDistance, Math.Sqrt(2) * betweenLineDistance);
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var lines = GetLines(pageWordsArr, maxDistWL).ToArray();
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// 3. Find blocks of text
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double maxDistBL = blMultiplier * betweenLineDistance;
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return GetLinesGroups(lines, maxDistBL).ToList();
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}
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/// <summary>
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/// Get information on the nearest point, filtered for angle.
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/// </summary>
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/// <param name="words"></param>
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/// <param name="pivot"></param>
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/// <param name="funcPivotDist"></param>
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/// <param name="funcPivotAngle"></param>
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/// <param name="funcPointsDist"></param>
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/// <param name="funcPointsAngle"></param>
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/// <param name="angleStart"></param>
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/// <param name="angleEnd"></param>
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/// <param name="finalDistMEasure"></param>
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/// <returns></returns>
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private double[] GetNearestPointData(Word[] words, Word pivot, Func<PdfRectangle,
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PdfPoint> funcPivotDist, Func<PdfRectangle, PdfPoint> funcPivotAngle,
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Func<PdfRectangle, PdfPoint> funcPointsDist, Func<PdfRectangle, PdfPoint> funcPointsAngle,
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double angleStart, double angleEnd,
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Func<PdfPoint, PdfPoint, double> finalDistMEasure)
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{
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var pointR = funcPivotDist(pivot.BoundingBox);
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var filtered = words.Where(w =>
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{
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var angleWL = Distances.Angle(funcPivotAngle(pivot.BoundingBox), funcPointsAngle(w.BoundingBox));
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return (angleWL >= angleStart && angleWL <= angleEnd);
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}).ToList();
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filtered.Remove(pivot); // remove itself
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if (filtered.Count > 0)
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{
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int index = pointR.FindIndexNearest(
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filtered.Select(w => funcPointsDist(w.BoundingBox)).ToList(),
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Distances.Euclidean, out double distWL);
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if (index >= 0)
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{
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var matchWL = filtered[index];
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return new double[]
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{
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(double)pivot.Letters.Select(l => l.FontSize).Mode(),
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finalDistMEasure(pointR, funcPointsDist(matchWL.BoundingBox))
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};
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}
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}
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return null;
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}
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/// <summary>
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/// Build lines via transitive closure.
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/// </summary>
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/// <param name="words"></param>
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/// <param name="maxDist"></param>
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/// <returns></returns>
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private IEnumerable<TextLine> GetLines(Word[] words, double maxDist)
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{
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TextDirection textDirection = words[0].TextDirection;
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var groupedIndexes = ClusteringAlgorithms.SimpleTransitiveClosure(words, Distances.Euclidean,
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(w1, w2) => maxDist,
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w => w.BoundingBox.BottomRight, w => w.BoundingBox.BottomLeft,
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w => true,
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(w1, w2) =>
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{
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var angleWL = Distances.Angle(w1.BoundingBox.BottomRight, w2.BoundingBox.BottomLeft); // compare bottom right with bottom left for angle
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return (angleWL >= -30 && angleWL <= 30);
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}).ToList();
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Func<IEnumerable<Word>, IReadOnlyList<Word>> orderFunc = l => l.OrderBy(x => x.BoundingBox.Left).ToList();
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if (textDirection == TextDirection.Rotate180)
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{
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orderFunc = l => l.OrderByDescending(x => x.BoundingBox.Right).ToList();
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}
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else if (textDirection == TextDirection.Rotate90)
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{
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orderFunc = l => l.OrderByDescending(x => x.BoundingBox.Top).ToList();
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}
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else if (textDirection == TextDirection.Rotate270)
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{
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orderFunc = l => l.OrderBy(x => x.BoundingBox.Bottom).ToList();
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}
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for (int a = 0; a < groupedIndexes.Count(); a++)
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{
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yield return new TextLine(orderFunc(groupedIndexes[a].Select(i => words[i])));
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}
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}
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/// <summary>
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/// Build blocks via transitive closure.
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/// </summary>
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/// <param name="lines"></param>
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/// <param name="maxDist"></param>
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/// <returns></returns>
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private IEnumerable<TextBlock> GetLinesGroups(TextLine[] lines, double maxDist)
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{
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var groupedIndexes = ClusteringAlgorithms.SimpleTransitiveClosure(lines, Distances.Euclidean,
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(l1, l2) => maxDist,
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l => l.BoundingBox.TopLeft, l => l.BoundingBox.BottomLeft,
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l => true, (l1, l2) => true).ToList();
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for (int a = 0; a < groupedIndexes.Count(); a++)
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{
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yield return new TextBlock(groupedIndexes[a].Select(i => lines[i]).ToList());
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}
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}
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/// <summary>
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/// Get the average distance value of the peak bucket of the histogram.
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/// </summary>
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/// <param name="values">array[0]=font size, array[1]=distance</param>
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/// <returns></returns>
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private double GetPeakAverageDistance(IEnumerable<double[]> values)
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{
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int max = (int)values.Max(x => x[1]) + 1;
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int[] distrib = new int[max];
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// Create histogram with buckets of size 1.
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for (int i = 0; i < max; i++)
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{
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distrib[i] = values.Where(x => x[1] > i && x[1] <= i + 1).Count();
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}
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var peakIndex = Array.IndexOf(distrib, distrib.Max());
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return values.Where(v => v[1] > peakIndex && v[1] <= peakIndex + 1).Average(x => x[1]);
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}
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}
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}
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