private void btnEuclidean_Click(object sender, EventArgs e)
{
var featureExtractor = new PointFloatShapeFeatureExtractor();
var preProc = new PreProcessing();
var traceGroup = _drawingInk.Ink.ToTraceGroup();
var sampledTraceGroup = preProc.ResampleTraceGroup(chkIsNormalized.Checked?preProc.NormalizeSize(traceGroup): traceGroup);
var features = featureExtractor.ExtractFeature(sampledTraceGroup);
var testTraceGroup = _resultInk.Ink.ToTraceGroup();
var sampledTestTraceGroup = preProc.ResampleTraceGroup(chkIsNormalized.Checked?preProc.NormalizeSize(testTraceGroup): testTraceGroup);
var testFeatures = featureExtractor.ExtractFeature(sampledTestTraceGroup);
var eucDistance = featureExtractor.ComputeEuclideanDistance(features, testFeatures);
MessageBox.Show(@"Euclidean Distance = " + eucDistance);
}
private void btnFeature_Click(object sender, EventArgs e)
{
var traceGroup = _resultInk.Ink.ToTraceGroup();
var featureExtractor = new PointFloatShapeFeatureExtractor();
var features = featureExtractor.ExtractFeature(traceGroup);
var str = new StringBuilder();
foreach (var feature in features)
{
str.AppendLine(string.Format("{0} {1} {2} {3} {4}", feature.X, feature.Y, feature.SinTheta, feature.CosTheta,
feature.IsPenUp));
}
str.AppendLine("--- Total Point = " + features.Count);
txtFeature.Text = str.ToString();
}
public TrainRecognizer()
{
_featureExtractor = new PointFloatShapeFeatureExtractor();
_inkFile = new InkFile();
_preProc = new PreProcessing();
}
private int _numOfChoice = 5; // K value in k-NN
public NNRecognizer()
{
_featureExtractor = new PointFloatShapeFeatureExtractor();
_preProc = new PreProcessing();
}
