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I am trying to develop a basic OCR for bangla character using openCV. I have used opencv's built-in CvKNearest object. everything works alright except the accuracy of recognition. I haven't used any pre-calculated feature. I have plan to use some more feature to increase the accuracy. I have made some googling to find which feature is used in Opencv's Knearest object for prediction, but I couldn't get that. could anyone please explain me Which feature vector does opencv's K-Nearest-Neighbor algorithm use to predict in pattern recognition?

Sourav
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If you are looking for what kind of features you need, there are lot .

  1. Statistical features - ex , normalized density values , zone method, # "on" pixels
  2. Structural features - ex , # intersections, # holes etc
  3. Projection histogram features etc

Like wise there are lot. Suggest you to read about few publications regarding OCR first, start from here example

Heshan Sandeepa
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