title: achieve better recognition results via training tesseract
body: <p>I have a question regarding achieving better recognition results with tesseract. I am using tesseract to recognize serial numbers. The serial numbes consist of only one font-type, characters A-Z, 0-9 and occur in different sizes and lengths. </p>
  
  <p>At the moment I am able to recognize about 40% of the serial number images correct. Images are taken via mobile phone camera. Therefore the image quality isn't the best. </p>
  
  <p>Special problem characters are 8/B, 5/6. Since I am recognizing only serial numbers, I am not using any dictionary improvements and every character is recognized independently.</p>
  
  <p>My question is: Does someone has already experience in achieving better recognition results with training tesseract? How many images would be needed to be able to get good results.</p>
  
  <p>For training tesseract should I use printed and afterwards photographed serial numbers, or should I use original digital serial numbers, without printing and photographing? </p>
  
  <p>Maybe somebody has already experience in that kind of area.</p>
  
  <p>Regarding training tesseract: I have already trained tesseract with some images. Therefore I have printed all characters in different sizes, photographed and labeled them correctly. Example training photo of the character 5 </p>
  
  <p><img src="https://i.stack.imgur.com/Gh6Fk.jpg" alt="enter image description here"></p>
  
  <p>Is this a good/bad training example? Since I only want to recognize single characters without any dependency, I though I don't have to use words for training. </p>
  
  <p>Actual I only have trained with 3 of these images for the characters <em>B 8 6 5</em> which doesn't result in a better recognition in comparison with the original english (eng) tesseract database. </p>
  
  <p>best regards, 
  Christoph</p>