title: Character detection from binary image
body: <p>Hello I'm trying to detect characters on this specific image.</p>
  
  <p>Original Image:</p>
  
  <p><img src="https://i.stack.imgur.com/NKlpk.png" alt="enter image description here"></p>
  
  <p>After some preprocessing I've finally got this image
  <img src="https://i.stack.imgur.com/LqPWG.png" alt="enter image description here"></p>
  
  <p>Currently I could detect single characters by using SURF feature detection and matching algorithm.</p>
  
  <p><img src="https://i.stack.imgur.com/uAUvc.png" alt="enter image description here"></p>
  
  <p>Also with template matching I could detect single characters.</p>
  
  <p><img src="https://i.stack.imgur.com/2umdM.png" alt="enter image description here"></p>
  
  <p>But with this algorithms I cannot really classify my matches to detect which character is what. 
  After some research and test I decided to use hog descriptors to extract and then train those descriptors with svm to classify.</p>
  
  <p>When I crop those chars for surf and template matching I manually cropped those chars in photshop so sizes are not equal to each other but Hog algorithm uses a specific width * height. so I have to have every characters with same size. </p>
  
  <p>So my question is since I am going to use those method only for the <strong>original image</strong> can I manually crop and resize every char for HOG ? or do I have to first detect each character extract them and then prepare those extracted characters for Hog? If the second one what kind of methods would you suggest me to use?</p>