private static List <Line> RecognizeLines(Bitmap bw, RecognitionOptions options)
{
List <Point> edgePoints = EdgePointExtraction.ExtractEdgePoints(bw);
List <RawLine> rawLines = PseudoHoughTransform.RecognizeLines(edgePoints, options);
return(LineFilter.FilterLines(edgePoints, rawLines, options));
}
/*
* Convenience function to recognize set of lines in points.
*/
public static List <RawLine> RecognizeLines(List <Point> points, RecognitionOptions options)
{
int[,] hough = HoughTransform(points, options);
List <Point> houghPeaks = FindHoughPeaks(hough, options);
return(ExtractRawLines(houghPeaks, options));
}
/*
* Convenience function to recognize table in an image.
*/
public static Option <Table> RecognizeTable(Bitmap sourceImage, List <double> columnWidthsHintOrNull = null)
{
Bitmap bw = ImageUtil.ToBlackAndWhite(sourceImage);
Bitmap rotBw = ImageUtil.RotateCounterClockwise(bw);
var horizOptions = RecognitionOptions.HorizontalOptions();
horizOptions.imageWidth = bw.Width;
horizOptions.imageHeight = bw.Height;
var vertOptions = RecognitionOptions.VerticalOptions();
vertOptions.imageWidth = rotBw.Width;
vertOptions.imageHeight = rotBw.Height;
List <Line> horizLines = RecognizeLines(bw, horizOptions);
List <Line> vertLines = RecognizeLines(rotBw, vertOptions);
if (horizLines.Count == 0 || vertLines.Count == 0)
{
return(new None <Table>());
}
else
{
var lnorm = new LineNormalization(horizLines, vertLines, sourceImage);
return(TableBuilder.NewBuilder(lnorm, Options.Create(columnWidthsHintOrNull)).table);
}
}
public static RecognitionOptions CommonOptions()
{
var options = new RecognitionOptions();
options.maxAngleFactor = 0.03f;
options.houghWindowWidth = 20;
options.houghWindowHeight = 10;
return(options);
}
/*
* Locate peaks in A/DO space array.
* For each point, searches some narrow window of points around it,
* and if there is no point bigger than current point, records it as a peak.
* If there are several points with same value, records their average as a peak.
*/
public static List <Point> FindHoughPeaks(int[,] hough, RecognitionOptions options)
{
int width = hough.GetLength(0);
int height = hough.GetLength(1);
int maxHough = 0;
foreach (var h in hough)
{
if (h > maxHough)
{
maxHough = h;
}
}
List <Point> thresholdedPoints = new List <Point>();
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
if ((double)hough[x, y] / maxHough > options.houghThreshold)
{
thresholdedPoints.Add(new Point(x, y));
}
}
}
List <Point> peaks = new List <Point>();
HashSet <Point> usedPoints = new HashSet <Point>();
foreach (Point pt in thresholdedPoints)
{
if (!usedPoints.Contains(pt))
{
List <Point> adjPoints =
thresholdedPoints
.Where(p =>
Math.Abs(p.X - pt.X) < options.houghWindowWidth &&
Math.Abs(p.Y - pt.Y) < options.houghWindowHeight).ToList();
int maxAdj = adjPoints.Select(p => hough[p.X, p.Y]).Max();
if (hough[pt.X, pt.Y] == maxAdj)
{
List <Point> adjPeaks = adjPoints.Where(p => hough[p.X, p.Y] == maxAdj).ToList();
int avgX = (int)Math.Round(adjPeaks.Select(p => p.X).Average());
int avgY = (int)Math.Round(adjPeaks.Select(p => p.Y).Average());
peaks.Add(new Point(avgX, avgY));
foreach (var adj in adjPoints)
{
usedPoints.Add(adj);
}
}
}
}
return(peaks);
}
/*
* Get array of angles that we want to test.
* Creates array of angles, that differ by 1px at distance of image width.
*/
private static double[] GetAngleMap(RecognitionOptions options)
{
int maxDy = (int)Math.Ceiling(options.imageWidth * options.maxAngleFactor);
double[] angleMap = new double[maxDy * 2 + 1];
for (int dy = -maxDy; dy <= maxDy; dy++)
{
angleMap[maxDy + dy] = (double)dy / (double)options.imageWidth;
}
return(angleMap);
}
/*
* Extract raw lines from peaks in A/DO space.
*/
public static List <RawLine> ExtractRawLines(List <Point> houghPeaks, RecognitionOptions options)
{
double[] angleMap = GetAngleMap(options);
List <RawLine> lines = new List <RawLine>();
foreach (var pt in houghPeaks)
{
lines.Add(new RawLine {
yInt = pt.Y, k = angleMap[pt.X]
});
}
return(lines);
}
/*
* Main function, that performs Pseudo-Hough transform as described above.
* Returns A/DO space array.
*/
public static int[,] HoughTransform(List <Point> points, RecognitionOptions options)
{
double[] angleMap = GetAngleMap(options);
int[,] hough = new int[angleMap.Length, options.imageHeight];
for (int a = 0; a < angleMap.Length; a++)
{
foreach (Point pt in points)
{
int y = (int)Math.Round(pt.Y - pt.X * angleMap[a]);
if (y >= 0 && y < options.imageHeight)
{
hough[a, y]++;
}
}
}
return(hough);
}
public static bool HasCyclicPatterns(bool[] linePoints, int from, int to, RecognitionOptions options)
{
for (int w = options.cyclicPatternsMinWidth; w <= options.cyclicPatternsMaxWidth; w++)
{
int[] acc = new int[w];
for (int i = from; i <= to; i++)
{
if (linePoints[i])
{
acc[(i - from) % w]++;
}
}
int threshold = (to - from) / w / 5;
double cyclicPatternSize = (double)acc.Where(a => a < threshold).Count() / w;
if (cyclicPatternSize > 0.2)
{
return(true);
}
}
return(false);
}
public static Bitmap CyclicPatternsInLines(List <Point> edgePoints, List <RawLine> rawLines, RecognitionOptions options)
{
rawLines = rawLines.OrderBy(l => l.yInt).ToList();
List <Bitmap> images = new List <Bitmap>();
foreach (var rawLine in rawLines)
{
bool[] linePoints = new bool[options.imageWidth];
foreach (var pt in edgePoints)
{
if (Math.Abs(rawLine.yInt - (pt.Y - pt.X * rawLine.k)) < 2)
{
linePoints[pt.X] = true;
}
}
var lines = SegmentDetector.GetSegments(linePoints, rawLine);
if (lines.Count > 0)
{
images.Add(CyclicPatternsImage(linePoints, lines.First().p1.X, lines.Last().p2.X));
}
}
return(ImageUtil.VerticalConcat(images));
}
/*
* Forms solid lines from set of raw lines.
* Discards lines that have cyclic patterns in them.
*/
public static List <Line> FilterLines(List <Point> edgePoints, List <RawLine> rawLines, RecognitionOptions options)
{
List <Line> lines = new List <Line>();
foreach (var rawLine in rawLines)
{
// convert rawLine to list of black/white pixels
bool[] linePoints = new bool[options.imageWidth];
foreach (var pt in edgePoints)
{
if (Math.Abs(rawLine.yInt - (pt.Y - pt.X * rawLine.k)) < 2)
{
linePoints[pt.X] = true;
}
}
var segments = SegmentDetector.GetSegments(linePoints, rawLine);
if (segments.Count > 0)
{
Line solidLine = SegmentDetector.GetSolidLine(segments);
if (!options.detectCyclicPatterns ||
!CyclicPatternDetector.HasCyclicPatterns(linePoints, solidLine.p1.X, solidLine.p2.X, options))
{
lines.Add(solidLine);
}
}
}
return(lines);
}
private void RunOCR(Bitmap sourceImage)
{
this.sourceImagePV.Image = sourceImage;
Bitmap bw = ImageUtil.ToBlackAndWhite(sourceImage);
this.bwImagePV.Image = bw;
Bitmap rotBw = ImageUtil.RotateCounterClockwise(bw);
this.rotBwImagePV.Image = rotBw;
var horizOptions = RecognitionOptions.HorizontalOptions();
horizOptions.imageWidth = bw.Width;
horizOptions.imageHeight = bw.Height;
var vertOptions = RecognitionOptions.VerticalOptions();
vertOptions.imageWidth = rotBw.Width;
vertOptions.imageHeight = rotBw.Height;
List <Point> horizEdgePoints = EdgePointExtraction.ExtractEdgePoints(bw);
this.edgePointsPV.Image = EdgePointExtraction.DrawPoints(bw, horizEdgePoints);
int[,] horizHough = PseudoHoughTransform.HoughTransform(horizEdgePoints, horizOptions);
List <Point> horizHoughPeaks = PseudoHoughTransform.FindHoughPeaks(horizHough, horizOptions);
Bitmap horizHoughPlainImage = PseudoHoughTransform.HoughTransformImage(horizHough);
Bitmap horizHoughImage = PseudoHoughTransform.HoughTransformImageWithPeaks(horizHough, horizHoughPeaks);
List <RawLine> horizRawLines = PseudoHoughTransform.ExtractRawLines(horizHoughPeaks, horizOptions);
List <Line> horizLines = LineFilter.FilterLines(horizEdgePoints, horizRawLines, horizOptions);
List <Point> vertEdgePoints = EdgePointExtraction.ExtractEdgePoints(rotBw);
this.rotEdgePointsPV.Image = EdgePointExtraction.DrawPoints(rotBw, vertEdgePoints);
int[,] vertHough = PseudoHoughTransform.HoughTransform(vertEdgePoints, vertOptions);
List <Point> vertHoughPeaks = PseudoHoughTransform.FindHoughPeaks(vertHough, vertOptions);
Bitmap vertHoughPlainImage = PseudoHoughTransform.HoughTransformImage(vertHough);
Bitmap vertHoughImage = PseudoHoughTransform.HoughTransformImageWithPeaks(vertHough, vertHoughPeaks);
List <RawLine> vertRawLines = PseudoHoughTransform.ExtractRawLines(vertHoughPeaks, vertOptions);
this.cyclicPatternsPV.Image = CyclicPatternDetector.CyclicPatternsInLines(vertEdgePoints, vertRawLines, vertOptions);
RecognitionOptions vertNoFilterOptions = vertOptions;
vertNoFilterOptions.detectCyclicPatterns = false;
List <Line> vertUnfilteredLines = LineFilter.FilterLines(vertEdgePoints, vertRawLines, vertNoFilterOptions);
List <Line> vertLines = LineFilter.FilterLines(vertEdgePoints, vertRawLines, vertOptions);
Bitmap rawLinesImage = DrawLines(bw, horizLines, vertUnfilteredLines, 2);
Bitmap filteredLinesImage = DrawLines(bw, horizLines, vertLines, 4);
this.filteredLinesPV.Image = filteredLinesImage;
this.houghPV.Image = ImageUtil.VerticalConcat(new List <Bitmap> {
ImageUtil.HorizontalConcat(new List <Bitmap> {
rawLinesImage, horizHoughImage, horizHoughPlainImage
}),
ImageUtil.RotateClockwise(vertHoughImage),
ImageUtil.RotateClockwise(vertHoughPlainImage)
});
var lnorm = new LineNormalization(horizLines, vertLines, sourceImage);
Bitmap normalizedLinesImage = DrawLines(bw, lnorm.normHorizLines, lnorm.normVertLines, 2);
this.normalizedLinesPV.Image = normalizedLinesImage;
var tb = TableBuilder.NewBuilder(lnorm, new None <List <double> >());
Bitmap tableRecognitionImage = tb.DebugImage(bw);
this.tableRecognitionPV.Image = tableRecognitionImage;
Option <Table> recognizedTable = tb.table;
recognizedTable.ForEach(table => {
Bitmap recognizedTableImage = new Bitmap(bw);
Graphics g = Graphics.FromImage(recognizedTableImage);
table.DrawTable(g, new Pen(Color.Red, 2));
g.Dispose();
this.recognizedTablePV.Image = recognizedTableImage;
});
if (recognizedTable.IsEmpty())
{
Console.WriteLine("no table was recognized");
}
this.recognizedTablePV.AddDoubleClickListener((pt, e) => {
recognizedTable.ForEach(table => {
table.GetCellAtPoint(pt.X, pt.Y).ForEach(cell => {
table.GetCellImage(bw, cell.X, cell.Y).ForEach(cellImage => {
new GradeRecognitionDebugView(cellImage, "<gen>").ShowDialog();
});
});
});
});
}
