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I have user tesseract ocr for my android project to recognize text from an image taken from the camera. But the results are not accurate. I want to optimize the image using opencv. I want to achieve the following for the captured image which is decoded in Bitmap.Config.ARGB_8888 format:

Detect the objects in the resized image.
Once the object is identified, compute its border w.r.t original image. (This is for removing the camera angle effect)
Extract the object from original image, by applying perspective transform.
Apply white balance to remove lightening effects.

In the example provided by with the tess_two api, they are using Leptonica for the image manipulations like drawing the bounding boxes around the words..But in my case I want to use OpenCV...Your guidance will be highly appreciated...

I have user tesseract ocr for my android project to recognize text from an image taken from the camera. But the results are not accurate. I want to optimize the image using opencv. I want to achieve the following for the captured image which is decoded in Bitmap.Config.ARGB_8888 format:

 
Detect the objects in the resized image.
image.
 
Once the object is identified, compute its border w.r.t original image. (This is for removing the camera angle effect)
effect)
 
Extract the object from original image, by applying perspective transform.
transform.
 
Apply white balance to remove lightening effects.

In the example provided by with the tess_two api, they are using Leptonica for the image manipulations like drawing the bounding boxes around the words..But in my case I want to use OpenCV...Your guidance will be highly appreciated...