private List <LingValue> GetAnswersForOneFinger(InputVector inputVector, double threshold) { List <LingValue> existingValuesQuality = new List <LingValue>(); existingValuesQuality.AddRange(Fuzzyficator.AverageQualityNfiqFuzzification(inputVector.AverageQuality)); existingValuesQuality.AddRange(Fuzzyficator.BackgroundFuzzification(inputVector.Background)); existingValuesQuality.AddRange(Fuzzyficator.DarknessFuzzification(inputVector.Darkness)); existingValuesQuality.AddRange(Fuzzyficator.LowQualityBlocksNfiqFuzzification(inputVector.BadBlocks)); List <LingValue> existingValuesFingerprint = EvaluateQuality(existingValuesQuality); existingValuesFingerprint.AddRange(Fuzzyficator.IdentityFuzzification(inputVector.Identity, threshold)); var result = EvaluateFinger(existingValuesFingerprint); return(result); }
private static void OneFingerTest(string fileName1, string fileName2) { var img1 = ImageHelper.LoadImage(Constants.PathToDb + fileName1); var img2 = ImageHelper.LoadImage(Constants.PathToDb + fileName2); double identity1 = Matcher.GetIdentity( fileName2, fileName1); var map = QualityHelper.GetQualityMap(Constants.PathToDb + fileName1); double awerageQuality = QualityHelper.GetAverageQualityNfiq(map); double badBlocks = QualityHelper.GetLowQualityBlocksNfiq(map); double darkness = QualityHelper.GetDarkness(img1); double background = QualityHelper.GetBackgroundPercentage(img1); InputVector input = new InputVector(); input.AverageQuality = awerageQuality; input.Background = background; input.BadBlocks = badBlocks; input.Darkness = darkness; input.Identity = identity1; DecisionMaker m = new DecisionMaker(); m.GetAnswerForFinger(input,0.5); }
internal static InputVector GetMonoFuzzyInput(string fileName1, string fileNameEt, QualityHelper qhelper) { //var img1 = ImageHelper.LoadImage(Constants.PathToDb + fileName1); //var imgEt = ImageHelper.LoadImage(Constants.PathToDb + fileNameEt); double identity1 = Matcher.GetIdentity(fileNameEt, fileName1); //var map = QualityHelper.GetQualityMap(Constants.PathToDb + fileName1); //double awerageQuality = QualityHelper.GetAverageQualityNfiq(map); //double badBlocks = QualityHelper.GetLowQualityBlocksNfiq(map); //double darkness = QualityHelper.GetDarkness(img1); //double background = QualityHelper.GetBackgroundPercentage(img1); InputVector input = new InputVector(); input.AverageQuality = qhelper.GetAverageQualityNfiqS(fileName1); input.Background = qhelper.GetBackgroundS(fileName1); input.BadBlocks = qhelper.GetLowQualityBlocksNfiqS(fileName1); input.Darkness = qhelper.GetDarknessS(fileName1); input.Identity = identity1; return input; }
private static void OneFingerTest(string fileName1, string fileName2) { var img1 = ImageHelper.LoadImage(Constants.PathToDb + fileName1); var img2 = ImageHelper.LoadImage(Constants.PathToDb + fileName2); double identity1 = Matcher.GetIdentity(fileName2, fileName1); var map = QualityHelper.GetQualityMap(Constants.PathToDb + fileName1); double awerageQuality = QualityHelper.GetAverageQualityNfiq(map); double badBlocks = QualityHelper.GetLowQualityBlocksNfiq(map); double darkness = QualityHelper.GetDarkness(img1); double background = QualityHelper.GetBackgroundPercentage(img1); InputVector input = new InputVector(); input.AverageQuality = awerageQuality; input.Background = background; input.BadBlocks = badBlocks; input.Darkness = darkness; input.Identity = identity1; DecisionMaker m = new DecisionMaker(); m.GetAnswerForFinger(input, 0.5); }
internal static InputVector GetMonoFuzzyInput(string fileName1, string fileNameEt, QualityHelper qhelper) { //var img1 = ImageHelper.LoadImage(Constants.PathToDb + fileName1); //var imgEt = ImageHelper.LoadImage(Constants.PathToDb + fileNameEt); double identity1 = Matcher.GetIdentity(fileNameEt, fileName1); //var map = QualityHelper.GetQualityMap(Constants.PathToDb + fileName1); //double awerageQuality = QualityHelper.GetAverageQualityNfiq(map); //double badBlocks = QualityHelper.GetLowQualityBlocksNfiq(map); //double darkness = QualityHelper.GetDarkness(img1); //double background = QualityHelper.GetBackgroundPercentage(img1); InputVector input = new InputVector(); input.AverageQuality = qhelper.GetAverageQualityNfiqS(fileName1); input.Background = qhelper.GetBackgroundS(fileName1); input.BadBlocks = qhelper.GetLowQualityBlocksNfiqS(fileName1); input.Darkness = qhelper.GetDarknessS(fileName1); input.Identity = identity1; return(input); }
public LingValue GetAnswerForFinger(InputVector inputVector, double threshold) { var results = GetAnswersForOneFinger(inputVector, threshold); return(FindMaxLingValue(results)); }
private List<LingValue> GetAnswersForOneFinger(InputVector inputVector, double threshold) { List<LingValue> existingValuesQuality = new List<LingValue>(); existingValuesQuality.AddRange(Fuzzyficator.AverageQualityNfiqFuzzification(inputVector.AverageQuality)); existingValuesQuality.AddRange(Fuzzyficator.BackgroundFuzzification(inputVector.Background)); existingValuesQuality.AddRange(Fuzzyficator.DarknessFuzzification(inputVector.Darkness)); existingValuesQuality.AddRange(Fuzzyficator.LowQualityBlocksNfiqFuzzification(inputVector.BadBlocks)); List<LingValue> existingValuesFingerprint = EvaluateQuality(existingValuesQuality); existingValuesFingerprint.AddRange(Fuzzyficator.IdentityFuzzification(inputVector.Identity, threshold)); var result = EvaluateFinger(existingValuesFingerprint); return result; }
public LingValue GetAnswerForFinger(InputVector inputVector, double threshold) { var results = GetAnswersForOneFinger(inputVector, threshold); return FindMaxLingValue(results); }