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We are trying automate the entire loan application and processing. So, this involved a lot of character recognition stuff as our target group have their financial documents as hard copies. Helping them autofill their information would make their task easier as well as avoid human errors while typing. So, after reading a few articles, I first designed a OCR using google’s OCR library tesseract. The classifier produced…
(Hopefully) Related question: What is the state of the art in OCR on photographs? Is there something like the inception model for OCR?
https://github.com/tensorflow/models/tree/master/attention_o...
We are trying automate the entire loan application and processing. So, this involved a lot of character recognition stuff as our target group have their financial documents as hard copies. Helping them autofill their information would make their task easier as well as avoid human errors while typing. So, after reading a few articles, I first designed a OCR using google’s OCR library tesseract. The classifier produced…
is it possible to share the images that did not work for you?
Earlier quoted context omitted.
is it possible to share the images that did not work for you?
We are majorly facing challenge with cheques and bank statements with noisy background. e.g. those of HDFC bank.
Teaseract is ok printed material that's neatly organized, but other than that it seems the only other programmatic ocr is google cloud vision. It's a hundred times better, but unfortunately I need to OCR documents I can't contractual show the mighty G
The best - and most expensive - solution is still Abbyy OCR. They provide an SDK than can be used locally.
A new local OCR solution is Anyline.io, but I have not used them yet.
We are trying automate the entire loan application and processing. So, this involved a lot of character recognition stuff as our target group have their financial documents as hard copies. Helping them autofill their information would make their task easier as well as avoid human errors while typing. So, after reading a few articles, I first designed a OCR using google’s OCR library tesseract. The classifier produced…
>It provided us the coordinates of all the texts and all we had to do was look for texts similar to an Account number and IFSC from a cheque book. Using some regex it was easy to find closely matching strings
Could you explain what you mean by this ? We are trying to read shopping receipts, but I have ZERO background in image processing... so have been trying to figure out what to do. I have been trying to use Google Vision API though.
>The one which worked best for us was a custom designed filter using Otsu’s Thresholding principle.
Is this where you pre-preocess the image to make it readable ? How does one do it - are these specialized tools or can I do this in python (like http://www.scipy-lectures.org/packages/scikit-image/auto_exa...)
We are trying automate the entire loan application and processing. So, this involved a lot of character recognition stuff as our target group have their financial documents as hard copies. Helping them autofill their information would make their task easier as well as avoid human errors while typing. So, after reading a few articles, I first designed a OCR using google’s OCR library tesseract. The classifier produced…
is this for US banks ? I'm assuming not. > It provided us the coordinates of all the texts and all we had to do was look for texts similar to an Account number and IFSC from a cheque book. Using some regex it was easy to find closely matching strings Could you explain what you mean by this ? We are trying to read shopping receipts, but I have ZERO background in image processing... so have been trying to figure out wh…