www.pudn.com > neuroocr_src.zip > Receptors.cs

// Neural Network OCR 
// 
// Copyright © Andrew Kirillov, 2005 
// andrew.kirillov@gmail.com 
// 
 
using System; 
using System.Drawing; 
using System.Collections; 
 
namespace NeuroOCR 
{ 
	/// 
 
	/// Receptors collection 
	/// 
 
	public class Receptors : CollectionBase 
	{ 
		private Random	rand = new Random(); 
		private Size	size = new Size(100, 100); 
 
		// Area size 
		public Size AreaSize 
		{ 
			get { return size; } 
			set { size = value; } 
		} 
		// Get receptor 
		public Receptor this[int index] 
		{ 
			get { return ((Receptor) InnerList[index]); } 
		} 
 
		// Constructor 
		public Receptors() 
		{ 
		} 
 
		// Add new receptor to the sequence 
		public void Add(Receptor receptor) 
		{ 
			InnerList.Add(receptor); 
		} 
 
		// Generate new receptors 
		public void Generate(int count) 
		{ 
			int	maxX = size.Width; 
			int maxY = size.Height; 
			int i = 0; 
 
			while (i < count) 
			{ 
				int x1 = rand.Next(maxX); 
				int y1 = rand.Next(maxY); 
				int x2 = rand.Next(maxX); 
				int y2 = rand.Next(maxY); 
 
				int	dx = x1 - x2; 
				int dy = y1 - y2; 
				int length = (int) Math.Sqrt(dx * dx + dy * dy); 
 
				// avoid too short and too long receptors 
				if ((length < 10) || (length > 50)) 
					continue; 
 
				InnerList.Add(new Receptor(x1, y1, x2, y2)); 
				i++; 
			} 
		} 
 
		// Get receptors state 
		public int[] GetReceptorsState(Bitmap image) 
		{ 
			int		width = image.Width; 
			int		height = image.Height; 
			int		n = InnerList.Count; 
			int[]	state = new int[n]; 
 
			for (int y = 0; y < height; y++) 
			{ 
				for (int x = 0; x < width; x++) 
				{ 
					// check for black pixel 
					if (image.GetPixel(x, y).R == 0) 
					{ 
						for (int i = 0; i < n; i++) 
						{ 
							// skip already activated receptors 
							if (state[i] == 1) 
								continue; 
 
							if (((Receptor) InnerList[i]).GetReceptorState(x, y)) 
								state[i] = 1; 
						} 
					} 
				} 
			} 
 
			return state; 
		} 
	} 
}