title: How to read electricity meter using Computer Vision + Tesseract?
body: <p>I have to write an app for reading an electricity meter (analog and digital).</p>
  
  <p>I'm starting with the analog. I read that I can use computer vision for preprocessing (threshold, find contours, etc), and then pass the detected characters to an OCR program like Tesseract. But I couldn't find the perfect detection methods. Sometimes it works for some images but I have to tune the parameters for the others.</p>
  
  <p>I checked out other apps like <a href="https://anyline.com/products/ocr-meter-reading/" rel="nofollow noreferrer">Anyline.com</a> which has great accuracy. How do I achieve such accuracy with traditional computer vision? Or should I go with machine/deep learning? Actually I'm no expert on this field. Have been exploring about a year. My background is regular apps (web, mobile) programming. So, any advice is highly appreciated.</p>
  
  <p>Here are some examples of my current effort:</p>
  
  <p><img src="https://i.stack.imgur.com/gmRPR.jpg" alt="Meter 1"> 
  <img src="https://i.stack.imgur.com/LHRDr.png" alt="Result 1"></p>
  
  <p><img src="https://i.stack.imgur.com/HnOp8.jpg" alt="Meter 2"> 
  <img src="https://i.stack.imgur.com/bxtDh.png" alt="Result 2"></p>
  
  <p><img src="https://i.stack.imgur.com/vIyYE.jpg" alt="Image 3">
  <img src="https://i.stack.imgur.com/jiEBq.png" alt="Result 3"></p>