Esempio n. 1
0
		private Candidate findCandidate(Image test)
		{
			double bestMSE = double.MaxValue;
			CharPattern bestCandidate = patterns[0];
			foreach(CharPattern train in patterns) 
			{
				double mse = calcMSE(train, test);
				if(mse < bestMSE) 
				{
					bestMSE = mse;
					bestCandidate = train;
				}
				
				if(mse == 0) 
				{
					break;
				}
			}
			return new Candidate(bestMSE, bestCandidate);
		}
Esempio n. 2
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        public static List <CharPattern> readCharsFromResources(string section)
        {
            // result
            List <CharPattern> patterns = new List <CharPattern>();

            // get a reference to the current assembly
            Assembly ass = Assembly.GetExecutingAssembly();

            // read from assembly
            Stream stream = getAssemblyStream(ass, "mapping.config");

            // config
            XmlDocument doc = new XmlDocument();

            doc.Load(stream);

            // parse
            XmlNode parent = doc.GetElementsByTagName(section).Item(0);

            foreach (XmlNode node in parent.ChildNodes)
            {
                // attributes
                XmlElement charElement = (XmlElement)node;
                char       name        = charElement.Attributes["key"].Value[0];
                string     file        = charElement.Attributes["image"].Value;

                // read from assembly
                Stream imgStream = getAssemblyStream(ass, file);
                Bitmap bitmap    = Bitmap.FromStream(imgStream) as Bitmap;
                Image  image     = toImage(bitmap);
                imgStream.Close();

                // new pattern
                CharPattern pattern = new CharPattern(name, image);
                patterns.Add(pattern);
            }

            return(patterns);
        }
Esempio n. 3
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		private Candidate findSubCandidate(Image test, int xOffset)
		{
			double bestMSE = double.MaxValue;
			CharPattern bestCandidate = patterns[0];
			
			foreach(CharPattern train in patterns)
			{					
				if(train.width > 2 && 
				   train.height <= test.height && 
				   (train.width + xOffset) <= test.width)
				{
					int distance = test.height - train.height;
					for(int y = 0; y <= distance; y++)
					{
						int xStart = xOffset;
						int xEnd = xStart + train.width;
						int yStart = y;
						int yEnd = yStart + train.height;
						Image subTest = test.crop(xStart, xEnd, yStart, yEnd);
						double mse = calcMSE(train, subTest);
							
						if(mse < bestMSE) 
						{
							bestMSE = mse;
							bestCandidate = train;
						}
						
						if(bestMSE == 0)
						{
							return new Candidate(bestMSE, bestCandidate);
						}
					}
				}
			}
			
			return new Candidate(bestMSE, bestCandidate);
		}
Esempio n. 4
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			public Candidate(double mse, CharPattern pattern)
			{
				this.mse = mse;
				this.pattern = pattern;
			}