public RecognizedChar Recognize(Character imgChar)
{
imgChar.Normalize();
List <double> output = Network.Test(imgChar.ExtractFeatures());
RecognizedChar recognized = new RecognizedChar();
for (int i = 0; i < output.Count; i++)
{
recognized.AddPattern(new RecognizedChar.RecognizedPattern(Alphabet[i], (float)output[i]));
}
recognized.Render();
recognized.Sort(1);
return(recognized);
}
public RecognizedChar Recognize(Character chr)
{
List <double> tested = chr.ExtractFeatures();
int minx = 0;
float minfx = float.PositiveInfinity;
RecognizedChar recognized = new RecognizedChar();
for (int x = 0; x < _learnLists.Count; x++)
{
float fx = SimplifiedEuclideanDistance(tested, _learnLists.ElementAt(x));
recognized.AddPattern(new RecognizedChar.RecognizedPattern(Alphabet[x], fx));
}
recognized.Sort(0);
return(recognized);
}
public override RecognizedChar Recognize(Char chr)
{
List <Double> tested = chr.ExtractFeatures();
RecognizedChar recognized = new RecognizedChar();
for (int x = 0; x < learnVectors.Count; x++)
{
Double fx = SimplifiedEuclideanDistance(tested, learnVectors[x]);
recognized.AddPattern(new CharacterRecognizer.RecognizedChar.RecognizedPattern(alphabet[x], fx));
}
recognized.Sort(0);
return(recognized);
}
