Пример #1
0
        public bool IsEqual(IClusterableItem item)
        {
            bool b1 = width == item.Width;
            bool b2 = height == item.Height;
            bool b3 = red == item.Red();
            bool b4 = green == item.Green();
            bool b5 = blue == item.Blue();

            return (b1 && b2 && b3 && b4 && b5);
        }
Пример #2
0
        public Dictionary<string, List<ArtImage>> Cluster()
        {
            IClusterableItem[] clusterPoints = new IClusterableItem[CLUSTER_COUNT];
            for (int i = 0; i < CLUSTER_COUNT; i++)
            {
                clusterPoints[i] = ClusterPoint.getRandomClusterPoint();
            }
            int loopCount = 0;
            bool ChangeOccurred = false;
            do
            {
                ChangeOccurred = false;
                foreach (ArtImage art_image in imagesToCluster)
                {
                    if (art_image != null)
                    {
                        double bestDistance = 10000;
                        string clusterName = "cluster0";
                        for (int i = 0; i < CLUSTER_COUNT; i++)
                        {
                            double currentDistance = getDistance(clusterPoints[i], art_image);
                            if (currentDistance <= bestDistance)
                            {
                                bestDistance = currentDistance;
                                clusterName = "cluster" + (i + 1);
                            }
                        }
                        clusters[clusterName].Add(art_image);
                    }
                }
                IClusterableItem[] newClusterPoints = new IClusterableItem[CLUSTER_COUNT];
                for (int i = 0; i < CLUSTER_COUNT; i++)
                {
                    String clusterNum = "cluster" + (i+1);
                    newClusterPoints[i] = getAverageClusterPointFromArtImageList(clusters[clusterNum]);
                }

                for (int i = 0; i < CLUSTER_COUNT; i++)
                {
                    if (!newClusterPoints[i].IsEqual(clusterPoints[i]))
                    {
                        ChangeOccurred = true;
                        clusterPoints[i] = newClusterPoints[i];
                    }
                }
                loopCount++;
                if (ChangeOccurred || loopCount < 200)
                {
                    clusters = new Dictionary<string, List<ArtImage>>();
                    CreateClusters();
                }
            }
            while (ChangeOccurred || loopCount < 200);
            return clusters;
        }
Пример #3
0
        public double getDistance(IClusterableItem image1, IClusterableItem image2)
        {
            double distance = 0;

            double heightDistance = Math.Pow((image2.Height - image1.Height), 2);
            double widthDistance = Math.Pow((image2.Width - image1.Width), 2);
            double redDistance = Math.Pow((image2.Red() - image1.Red()), 2);
            double greenDistance = Math.Pow((image2.Green() - image1.Green()), 2);
            double blueDistance = Math.Pow((image2.Blue() - image1.Blue()), 2);

            distance = Math.Sqrt((heightDistance + widthDistance + redDistance + greenDistance + blueDistance));

            return distance;
        }