public void Execute()
{
Console.WriteLine("Execute OCR");
OCR.Statistics.Clear();
OCR.Statistics.AddCounter("Processors", System.Environment.ProcessorCount);
SISThreshold filter = new SISThreshold();
int Threshold = filter.CalculateThreshold(m_Image.Image, m_Image.Area);
OtsuThreshold filterOtsu = new OtsuThreshold();
Threshold = filterOtsu.CalculateThreshold(m_Image.Image, m_Image.Area);
PreprocessPage Processor = new PreprocessPage();
Processor.Image = m_Image;
Processor.Treshold = m_Image.CalculateOtsuThreshold();
m_Image.Threshold = 170;
Processor.Execute();
resultBitmap = PageImage.CreateBitmapFromByteArray(m_Image.BinaryBytes, new Size(m_Image.Width, m_Image.Height));
DetectComponents Step2 = new DetectComponents();
Step2.Image = m_Image;
Step2.Execute();
AnalyseComponents Step3 = new AnalyseComponents();
Step3.Image = m_Image;
Step3.Execute();
DetectSentences Step4 = new DetectSentences();
Step4.Image = m_Image;
Step4.Execute();
ExtractFeatures Step5 = new ExtractFeatures();
Step5.Image = m_Image;
Step5.Execute();
RecogniseComponent Step6 = new RecogniseComponent();
Step6.Image = m_Image;
Step6.Execute();
ProcessSentences Step7 = new ProcessSentences();
Step7.Image = m_Image;
Step7.Execute();
}
/// <summary>
/// This functions 'recognises' the given compontent by running its features through
/// a neural network.
/// </summary>
/// <param name="Component"></param>
public static void RecogniseWithoutConnectedRepair(ShapeNet ShapeNet, PageComponent Component)
{
sNeuralOutput Result = new sNeuralOutput();
ShapeNet.NeuralNetwork.ComputeOutput(RecogniseComponent.CalculateNetworkInput(Component), Result);
for (int i = 0; i < Result.fOutputs.Count; i++)
{
if (Result.fOutputs[i] >= 0.01)
{
Component.AddRecognitionResult(Result.fOutputs[i], ShapeNet.ShapeList[i].Shape);
}
}
}
/// <summary>
/// This functions splits a character in multiple components. Used for splitting connected characters
/// </summary>
public void Split(ShapeNet ShapeNet)
{
List <int> SplitLines;
//Step 1: Get the position for possible splits
SplitLines = SplitDeterminePositions();
if (SplitLines.Count == 0)
{
return;
}
RecognitionResults.Clear();
//Step 2: Find the combination of the best (highest scores) recognised components
List <PageComponent> Components = new List <PageComponent>(0);
PageComponent newComponent;
PageComponent prevComponent;
Rectangle SplitArea;
int start, end;
SplitLines.Insert(0, 0);
SplitLines.Add(Width - 1);
start = 0;
end = 1;
while (end < SplitLines.Count)
{
SplitArea = new Rectangle(SplitLines[start] + 1, 0, SplitLines[end] - SplitLines[start] - 2, Height);
if (SplitArea.Width > 0 && SplitArea.Height > 0)
{
while (NumberPixelsOnRow(BinaryBytes, SplitArea, 0, 0) == 0)
{
SplitArea.Y = SplitArea.Y + 1;
SplitArea.Height = SplitArea.Height - 1;
}
while (NumberPixelsOnRow(BinaryBytes, SplitArea, SplitArea.Height - 1, 0) == 0)
{
SplitArea.Height = SplitArea.Height - 1;
}
newComponent = PartialCopy(SplitArea);
ExtractFeatures.ExecuteExtractFeatures(newComponent, false);
RecogniseComponent.RecogniseWithoutConnectedRepair(ShapeNet, newComponent);
if (Components.Count > 0 && end - start > 1)
{
prevComponent = Components.Last();
if (prevComponent.ContentProbability < newComponent.ContentProbability && newComponent.Content != "connected" && newComponent.Content != "garbage")
{
Components.Remove(prevComponent);
Components.Add(newComponent);
}
else
{
start = end - 1;
end--;
}
}
else
{
Components.Add(newComponent);
}
}
end++;
}
//Add the new recognition result
RecognitionResult newResult;
newResult = new RecognitionResult();
newResult.Content = "";
newResult.Probability = 0;
foreach (PageComponent Component in Components)
{
newResult.Content += Component.Content;
newResult.Probability += Component.ContentProbability;
}
newResult.Probability = newResult.Probability / Components.Count;
RecognitionResults.Add(newResult);
//Save a copy of the image to the disc
if (DebugTrace.DebugTrace.TraceFeatures)
{
String ComponentID = "000000" + ID;
ComponentID = ComponentID.Substring(ComponentID.Length - 6);
foreach (int SplitLine in SplitLines)
{
int pointer = SplitLine;
for (int y = 0; y < Height; y++)
{
if (BinaryBytes[SplitLine, y] == 0xFF)
{
BinaryBytes[SplitLine, y] = 0x10;
}
pointer += Stride;
}
}
Bitmap Bitmap = DebugTrace.DebugTrace.CreateBitmapFromByteArray(BinaryBytes, new Size(Width, Height));
String Filename = DebugTrace.DebugTrace.TraceFeatureFolder + "image_" + ComponentID + "_split.bmp";
Bitmap.Save(Filename);
}
}