Handwritten Text Recognition With KlearStack

Handwritten Text Recognition With KlearStack

The concept of optical character recognition is now very widely known and understood. However, handwritten text recognition is still an area of open research, for which multiple algorithms have been developed to date to facilitate the automatic capturing of text in documents.

Handwritten text recognition features based on neural networks have now gained acceptance and popularity, such that many applications are now using the same principle. The only shortcoming is that the collaboration of other technologies like natural language processing, deep learning, and computer vision is not effective enough in the algorithms developed so far for handwriting recognition. This ultimately translates into inaccuracies and inefficiencies in the OCR procedure.

KlearStack, on the other hand, uses a very unique handwriting recognition algorithm. Primarily, our algorithm is prepared with very specific feature vectors that drive highly accurate outputs.

Moreover, our emphasis on utilizing NLP, deep learning, and computer vision methodologies helps in implementing additive image processing, which enables our solution to handle multiple characters within the same image, be it handwritten or printed.

Thus, the output generated by our AI-based OCR solution is precise, even when the handwriting in the concerned document is almost illegible.

1.   Pre-printed Forms

Even while most businesses have shifted their processes online, a large chunk of our population still depends on pre-printed forms to initiate several key processes. These processes include opening a bank account, applying for a loan, applying for a government document, etc.

Since automation is imperative for faster processing, there needs to be a mechanism by which the handwritten text portion of these forms can be digitized instantly and accurately.

KlearStack’s OCR solution facilitates this process very accurately in two ways. Firstly, the OCR solution uses an algorithm that very accurately determines and distinguishes between the printed and handwritten components.

Secondly, by utilizing the natural language processing context, our tool starts recognizing the legible characters and alphabets written in the fields given in the form.

After that, it automatically makes sense out of it to predict the whole word accurately.

This is an important aspect of handwriting recognition because many forms are filled in illegible handwriting where not only the commonly available OCR tools but even we as readers might get confused.

2.   Printed Documents With Handwritten Text

You must have seen several official notices and circulars that were printed in the first place, but since there were corrections and updates required, the concerned authority decided to simply write it over the existing notice and convey it to the readers.

In such cases, if the organization wants to take the entire notice online and rectify it with all the new corrections and updates, it will be difficult for any simple traditional OCT to assist with that. This is because most OCR tools use a handwriting recognition algorithm that is not sound enough to distinguish random handwritten characters.

Here’s where KlearStack gives you a big edge. Primarily, the handwritten text detection feature is so accurate that you will not even experience a single spelling mistake in the output text.

Moreover, even if the handwritten corrections are added to the original document in a haphazard manner, artificial intelligence techniques used to develop our OCR solution make it possible to align the entire text to form a meaningful output.

The handwriting recognition algorithm works for detecting other components like signatures and stamps as well.

3.   Completely Handwritten Documents

To accurately extract text from completely handwritten documents, KlearStack’s OCR solution performs processing in several high-value steps. The first step is image pre-processing where noise elements are removed from the image to make the text clearer.

Further, the solution then makes a  bitmap image representation and then performs feature extraction through the character classification system. This process in itself has been so rigorously tested that we are certain that it can give a 95% accurate output every time.

KlearStack is also one of those very few OCR solutions that also accommodate different styles, text sizes, and alignments to form a digitized output with accurate representation. Most of the handwritten characters are easily recognized by our extensively trained machine learning models. Further, it is also a top performer when it comes to symbol recognition in completely handwritten documents.

Try Handwritten Text Recognition With KlearStack Today!

KlearStack’s handwritten text recognition system has been creatively designed and rigorously tested. Our machine learning models were trained with various types of handwritten text inputs to allow them to generalize seamlessly across different kinds of documents. We use the best classification systems that empower our AI-based OCR solution to complete feature extraction impeccably.

With our accuracy currently being over 95%, we aim to feed more samples and languages to our machine learning models to expand our scope of practice. This is the reason why many global enterprises dealing in insurance documents, banking papers, etc., prefer OCR to process their forms and other handwritten documents.

Ashutosh Saitwal
Ashutosh Saitwal
www.klearstack.com/

Ashutosh is the founder and director of the award winning KlearStack AI platform. You can catch him speaking at NASSCOM events around the world where he speaks and is an evangelist for RPA, AI, Machine Learning and Intelligent Document Processing.