It depends. Extent of automation will depend upon your images. If all of your images are same in size, then you can find coordinates of your sections (Like header, store address, billing info) and use a tool (for ex. imagemagick) to crop all of your images. Do OCR and then see what needs to be looked at.
if your images are of different sizes that you may have to do some kind of image processing to rescale, resize and many other things, which will gain depend upon the variations. On Thursday, December 8, 2016 at 1:13:14 PM UTC+5:30, Marie wrote: > > Thank you Ashish for the suggestion. > > The challenge is how to automate this process, any thoughts? > > > On Wednesday, December 7, 2016 at 1:00:59 AM UTC-8, Ashish Goel wrote: > >> Crop image into sub images and then OCR. Crop it in different segments. >> >> On Saturday, December 3, 2016 at 5:54:51 PM UTC+5:30, Marie wrote: >>> >>> Hi, >>> >>> We are trying to recognize receipt using Tesseract (v3.02 on >>> Windows). Tried to process the images but the words accuracy (comparing >>> with OneNote's result) is still not good. >>> >>> Any suggestions on how to improve accuracy? >>> >>> >>> p.s.attaching the raw image, processed image with OCR results by >>> Tesseract, >>> >>> raw image: >>> >>> >>> >>> text recognized from raw image: >>> >>> >>> >>> >>> >>> processed image (scaled 200%, increased contrast, cropped border) >>> >>> Thanks, >>> Marie >>> >>> -- You received this message because you are subscribed to the Google Groups "tesseract-ocr" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/tesseract-ocr. To view this discussion on the web visit https://groups.google.com/d/msgid/tesseract-ocr/4c9cb15e-3bec-4c0f-8e50-a553f01fd786%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
