title: What should I use for monospaced digits recognition?
body: <p>I have to recognize digits within an image from video stream and there are several more things, that should make recognition easier:<br>
  1) it is fixed font 6x8, all symbols are equal width<br>
  2) I know exact positions of digits, they are always rectangular, are not rotated/sqewed/scaled, but there may be some distortions because of air transmission glitch.<br>
  3) It is only digits and .<br>
  4) digit background is semi black (50% opaque)</p>
  
  <p>I've tried tesseract v2 and v3, but .NET wrappers aren't perfect and recognition error was very large, even if I trained with custom font, as far as I understand that is because of small resolution.</p>
  
  <p>I've made very simple algorithm by my self by turning image to black and white and counting matching pixels between original font image and image from stream, it performs better than tesseract, but I hink more sophisticated algorithm would do better.</p>
  
  <p>I've tried to train AForge using ActivationNetwork with BackPropagationLearning and it fails to converge(this article first part, as long as I don't need scaling and several fonts <a href="http://www.codeproject.com/Articles/11285/Neural-Network-OCR" rel="nofollow">http://www.codeproject.com/Articles/11285/Neural-Network-OCR</a>, as I understand code in article is for older version of AForge), bad thing is, that this project is not supported anymore, forum is closed and google groups as I understand too.</p>
  
  <p>I know there's OpenCV port to .NET, as far as I see, it has different network approaches than AForge, so questiton is which approach would fit best.</p>
  
  <p>So is there any .NET framework to help me at this, and if it supports more than one neural network implementations, which implementation would fit best?</p>