android - Optimize an image for text recognition using tesseract -


i have user tesseract ocr android project recognize text image taken camera. results not accurate. want optimize image using opencv. want achieve following captured image decoded in bitmap.config.argb_8888 format:

  1. detect objects in resized image.
  2. once object identified, compute border w.r.t original image. (this removing camera angle effect)
  3. extract object original image, applying perspective transform.
  4. apply white balance remove lightening effects.

in example provided tess_two api, using leptonica image manipulations drawing bounding boxes around words..but in case want use opencv...your guidance highly appreciated...

that's lot asking for, , depending on object may impossible. should check out tutorials on 2d feature detection , object detection (http://docs.opencv.org/doc/tutorials/features2d/table_of_content_features2d/table_of_content_features2d.html , http://docs.opencv.org/doc/tutorials/objdetect/table_of_content_objdetect/table_of_content_objdetect.html) see if there can use.

white balance not lighting, should adaptive thresholding or kind of high pass filtering instead.


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