public LBPCreator(ImageGrayData imageData, bool isTeaching, bool isDivideToFragments, bool isMultithread = true)
        {
            var needSize = RecognitionParameters.RecognitionFragmentSize;
            if (isTeaching)
            {
                needSize = RecognitionParameters.FragmentsSize;
            }

            if ((imageData.Width < needSize) ||
                (imageData.Height < needSize))
            {
                throw new ArgumentException("Размер изображения меньше размера фрагмента для разбиения. \n" +
                    "Невозможно создать LBP-гистограмму");
            }

            fragmentSize = needSize;
            this.isTeaching = isTeaching;
            this.isDivideToFragments = isDivideToFragments;
            this.isMultithread = isMultithread;
            data = imageData.Data;
            width = imageData.Width;
            height = imageData.Height;
            feature = null;
            ConstructFeature();
        }
        public LBPCreator(ImageGrayData imageData, bool isTeaching, bool isDivideToFragments, bool isMultithread = true)
        {
            var needSize = RecognitionParameters.RecognitionFragmentSize;

            if (isTeaching)
            {
                needSize = RecognitionParameters.FragmentsSize;
            }

            if ((imageData.Width < needSize) ||
                (imageData.Height < needSize))
            {
                throw new ArgumentException("Размер изображения меньше размера фрагмента для разбиения. \n" +
                                            "Невозможно создать LBP-гистограмму");
            }

            fragmentSize             = needSize;
            this.isTeaching          = isTeaching;
            this.isDivideToFragments = isDivideToFragments;
            this.isMultithread       = isMultithread;
            data    = imageData.Data;
            width   = imageData.Width;
            height  = imageData.Height;
            feature = null;
            ConstructFeature();
        }
 public TextureSample(ImageGrayData imageData, bool isDivideToFragments)
 {
     sample = imageData;
     var glcmCreator = new GLCMCreator(sample, false, isDivideToFragments);
     var lbpCreator = new LBPCreator(sample, false, isDivideToFragments);
     glcm = glcmCreator.Feature;
     lbp = lbpCreator.Feature;
 }
        public TextureSample(ImageGrayData imageData, bool isDivideToFragments)
        {
            sample = imageData;
            var glcmCreator = new GLCMCreator(sample, false, isDivideToFragments);
            var lbpCreator  = new LBPCreator(sample, false, isDivideToFragments);

            glcm = glcmCreator.Feature;
            lbp  = lbpCreator.Feature;
        }
Example #5
0
 private void AddFeatures(GLCMFeature glcm, LBPFeature lbp, string path)
 {
     lock ((knownFiles as ICollection).SyncRoot)
     {
         ++featuresCount;
         glcmFeatures.Add(glcm);
         lbpFeatures.Add(lbp);
         knownFiles.Add(path);
     }
 }
        public double GetDistance(LBPFeature other)
        {
            double result = 0;

            for (int i = 0; i < 18; ++i)
            {
                result += MathHelpers.Sqr(data[i] - other[i]) / (data[i] + other[i]);
            }
            return(result);
        }
 private void ConstructFeature()
 {
     if (isDivideToFragments)
     {
         var list = GetSubfeatures();
         feature = LBPFeature.BuildStandart(list);
     }
     else
     {
         feature = GetLBPFeature(new Fragment(0, 0, width, height));
     }
 }
Example #8
0
        public LBPFeature PrepareLBP(out double average, out double variance)
        {
            var lStandart  = LBPFeature.BuildStandart(lbpFeatures);
            var lDistances = new double[lbpFeatures.Count];

            for (int i = 0; i < lbpFeatures.Count; ++i)
            {
                lDistances[i] = lStandart.GetDistance(lbpFeatures[i]);
            }

            average  = MathHelpers.GetAverage(lDistances, 0, lbpFeatures.Count);
            variance = MathHelpers.GetVariance(lDistances, average, 0, lbpFeatures.Count);

            return(lStandart);
        }
Example #9
0
        public List <int> DischargeLBP(LBPFeature standart, double average, double variance)
        {
            var result = new List <int>();
            var tValue = alglib.studenttdistribution(lbpFeatures.Count - 1, RecognitionParameters.CompactFactor);

            var deviation = Math.Sqrt(variance);

            for (int i = 0; i < lbpFeatures.Count; ++i)
            {
                var value = Math.Abs(standart.GetDistance(lbpFeatures[i]) - average) / deviation;
                if (value > tValue)
                {
                    result.Add(i);
                }
            }

            return(result);
        }
Example #10
0
        internal void LoadKnowledges(XmlNode node)
        {
            Name = node.Attributes["name"].Value;
            int r, g, b;

            int.TryParse(node.Attributes["R"].Value, out r);
            int.TryParse(node.Attributes["G"].Value, out g);
            int.TryParse(node.Attributes["B"].Value, out b);
            RegionColor = Color.FromArgb(r, g, b);
            var samples = node.ChildNodes;

            foreach (XmlNode item in samples)
            {
                var file = item.ChildNodes[0].Attributes["path"].Value;
                var glcm = new GLCMFeature();
                glcm.LoadKnowledges(item.ChildNodes[1]);
                var lbp = new LBPFeature();
                lbp.LoadKnowledges(item.ChildNodes[2]);
                AddFeatures(glcm, lbp, file);
            }
        }
 private void ConstructFeature()
 {
     if (isDivideToFragments)
     {
         var list = GetSubfeatures();
         feature = LBPFeature.BuildStandart(list);
     }
     else
     {
         feature = GetLBPFeature(new Fragment(0, 0, width, height));
     }
 }
 public double GetDistance(LBPFeature other)
 {
     double result = 0;
     for (int i = 0; i < 18; ++i)
     {
         result += MathHelpers.Sqr(data[i] - other[i]) / (data[i] + other[i]);
     }
     return result;
 }
Example #13
0
 private void AddFeatures(GLCMFeature glcm, LBPFeature lbp, string path)
 {
     lock ((knownFiles as ICollection).SyncRoot)
     {
         ++featuresCount;
         glcmFeatures.Add(glcm);
         lbpFeatures.Add(lbp);
         knownFiles.Add(path);
     }
 }
Example #14
0
 internal void LoadKnowledges(XmlNode node)
 {
     Name = node.Attributes["name"].Value;
     int r, g, b;
     int.TryParse(node.Attributes["R"].Value, out r);
     int.TryParse(node.Attributes["G"].Value, out g);
     int.TryParse(node.Attributes["B"].Value, out b);
     RegionColor = Color.FromArgb(r, g, b);
     var samples = node.ChildNodes;
     foreach (XmlNode item in samples)
     {
         var file = item.ChildNodes[0].Attributes["path"].Value;
         var glcm = new GLCMFeature();
         glcm.LoadKnowledges(item.ChildNodes[1]);
         var lbp = new LBPFeature();
         lbp.LoadKnowledges(item.ChildNodes[2]);
         AddFeatures(glcm, lbp, file);
     }
 }
Example #15
0
        public List<int> DischargeLBP(LBPFeature standart, double average, double variance)
        {
            var result = new List<int>();
            var tValue = alglib.studenttdistribution(lbpFeatures.Count - 1, RecognitionParameters.CompactFactor);

            var deviation = Math.Sqrt(variance);
            for (int i = 0; i < lbpFeatures.Count; ++i)
            {
                var value = Math.Abs(standart.GetDistance(lbpFeatures[i]) - average) / deviation;
                if (value > tValue)
                {
                    result.Add(i);
                }
            }

            return result;
        }