private RecoResult combineResults(List <SymbolRank> topPolar, RecoResult screenResults, int numToReturn)
{
List <SymbolRank> fusionResults = new List <SymbolRank>();
foreach (SymbolRank sr in topPolar)
{
SymbolRank part_haus = screenResults.getSR(ResultType.PARTIAL_HAUSDORFF, sr.Symbol);
double part_haus_distance = screenResults.Normalize(ResultType.PARTIAL_HAUSDORFF, part_haus);
SymbolRank mod_haus = screenResults.getSR(ResultType.MOD_HAUSDORFF, sr.Symbol);
double mod_haus_distance = screenResults.Normalize(ResultType.MOD_HAUSDORFF, mod_haus);
SymbolRank tanim = screenResults.getSR(ResultType.TANIMOTO, sr.Symbol);
double tanim_distance = screenResults.Normalize(ResultType.TANIMOTO, tanim);
SymbolRank yule = screenResults.getSR(ResultType.YULE, sr.Symbol);
double yule_distance = 1 - screenResults.Normalize(ResultType.YULE, yule);
double distance = part_haus_distance + mod_haus_distance + tanim_distance + yule_distance;
fusionResults.Add(new SymbolRank(distance, sr.Symbol, sr.BestOrientation));
}
// sort
var sortedResults = from result in fusionResults
orderby result.Distance ascending
select result;
RecoResult combinedResults = new RecoResult();
combinedResults.AddRange(ResultType.FUSION, sortedResults.Take(numToReturn));
return(combinedResults);
}
public object Clone()
{
SymbolRank rank = (SymbolRank)this.MemberwiseClone();
rank._symbol = (BitmapSymbol)this._symbol.Clone();
return(rank);
}
private void polarRecognition(List <BitmapSymbol> defns)
{
foreach (BitmapSymbol bs in defns)
{
SymbolRank polar_result = Polar_Mod_Hausdorff(bs);
_results.Add(ResultType.POLAR, polar_result);
}
}
/// <summary>
/// Normalizes the distance of an existing symbol rank in relation to the values of
/// a particular type.
/// </summary>
/// <param name="type">The type to normalize in relation to.</param>
/// <param name="SR">The SymbolRank to normalize.</param>
/// <returns>A copy of the SymbolRank, except the distance has been normalized.</returns>
public double Normalize(ResultType type, SymbolRank SR)
{
double min = Best(type).Distance;
double max = Worst(type).Distance;
if (Math.Abs(max - min) < double.Epsilon)
{
return(double.PositiveInfinity);
}
return((SR.Distance - min) / (max - min));
}
private RecoResult polarRecognition(List <BitmapSymbol> defns)
{
RecoResult results = new RecoResult();
foreach (BitmapSymbol bs in defns)
{
SymbolRank polar_result = Polar_Mod_Hausdorff(bs);
results.Add(ResultType.POLAR, polar_result);
}
return(results);
}
private void combineResults()
{
List <SymbolRank> topPolar = _results.BestN(ResultType.POLAR, NUM_TOP_POLAR_TO_KEEP);
foreach (SymbolRank sr in topPolar)
{
double distance = 0.0;
SymbolRank part_haus = _results.getSR(ResultType.PARTIAL_HAUSDORFF, sr.Symbol);
distance += _results.Normalize(ResultType.PARTIAL_HAUSDORFF, part_haus);
SymbolRank mod_haus = _results.getSR(ResultType.MOD_HAUSDORFF, sr.Symbol);
distance += _results.Normalize(ResultType.MOD_HAUSDORFF, mod_haus);
SymbolRank tanim = _results.getSR(ResultType.TANIMOTO, sr.Symbol);
distance += 1 - _results.Normalize(ResultType.TANIMOTO, tanim);
SymbolRank yule = _results.getSR(ResultType.YULE, sr.Symbol);
distance += 1 - _results.Normalize(ResultType.YULE, yule);
_results.Add(ResultType.FUSION, new SymbolRank(distance, sr.Symbol, sr.BestOrientation));
}
}
public void Add(ResultType type, SymbolRank result)
{
_results[type].Add(result);
_results[type].Sort(delegate(SymbolRank SR1, SymbolRank SR2) { return(SR1.Distance.CompareTo(SR2.Distance)); });
}
public void Add(ResultType type, SymbolRank result)
{
_results[type].Add(result);
}
