Handwriting Recognition: Extracting More Out Of Your Documents

Handwriting Recognition: Extracting More Out Of Your Documents

What would you do if you were given a task to feed the entire data stored in a handwritten document into the computer by the end of the day? If you’ve been late to catch up with advancing trends, you will go about transcribing the full handwritten document and keep typing it throughout the day.

As you can understand, by opting for this method you will be in a position where you are bound to make mistakes and the final version will be full of errors. The point remains that the need in such situations is for software that helps you to directly extract information from a handwritten document and convert it into a machine-readable form. This process, in a nutshell, is known as handwriting recognition. Let us try and understand handwriting recognition in more detail, how it works, and what all benefits it can offer to organizations.

The automated recognition of characters in handwritten documents and the subsequent extraction of information is termed handwriting recognition. Currently, handwriting recognition is said to be a field of research, encompassing the methodologies used in artificial intelligence, computer vision, machine learning, etc. From a simple and basic optical character recognition tool, to an advanced intelligent character recognition system, you can spot the application of handwriting recognition everywhere.

Automated handwritten script recognition is based on similar lines as algorithm-based image recognition. Here, each handwritten character is thought of as an image input, and the output generated after processing indicates the class to which the image belongs.

Use Cases For Handwriting Recognition

● Healthcare Industry

Like all other working professionals, doctors, medical staff in hospitals and pharmacists to are habitual of giving prescriptions and writing patients’ medical notes in a handwritten mode only. This makes it difficult for health centers and hospitals to update the central database with recent medical records. With handwriting recognition software, the process of extracting information out of prescriptions becomes possible. They automate the extraction process and make vital information available in a digitized form.

● Banking Sector

The most widely used form of transaction for large-scale payments is cheque payment. Even while the popularity of net banking has increased significantly over the last few years, the percentage of people using cheque-based transaction methods is very high. In most banking setups, the method for processing cheque payments involves an employee who reads and then types the entire data on the cheque and then initiates the transaction from his end.

Over the years, this manual handling has been subject to a lot of criticism, primarily because of the amount of errors that it is prone to. So, a handwriting recognition app can be a great help in this domain, where the data present in cheques can be lifted as it is without any changes whatsoever, and can be updated in the necessary portals to initiate transactions.

● Insurance Sector

Any insurance company around the world receives an influx of thousands of documents monthly. These documents still contain a heavy load of handwritten components. If the processing of handwritten documents is not quick enough in the insurance sector, the claim settlement process usually takes a hit. This is the most dreaded scenario in this industry because it makes the company liable for legal action as well. This is the reason why the insurance sector is making use of handwriting recognition software very extensively to expedite data extraction and processing.

● E-Libraries

Online libraries are becoming extremely popular across the globe. The only problem with such libraries is that they do not provide the digitized form of old and historic text very commonly. The reason for this is pretty simple, most of the old text is either handwritten or the print is extremely faded. Therefore, converting the handwritten characters into machine-encoded text is crucial to creating ebooks for an online library. This necessitates the use of handwriting recognition software in this business.

Methods Of Using Handwriting Recognition

● Online Methods

Since online methods of handwriting recognition use a digital pen or stylus for stroke recognition, the ultimate result of data extraction using these methods is usually very accurate. These handwriting recognition devices help in the extraction of data while it is being written. The reason for this is that with the help of a digital pen, the software gets access to a lot of high-utility data needed for satisfactory character recognition.

● Offline Methods

Offline handwriting recognition systems involve the scanning of pre-written documents. Traditional applications like the optical character recognition software were designed to facilitate this type of recognition. The only problem with traditional software is that the errors incurred during conversion are extremely high. Therefore, there needs to be an addition and upgradation in these tools to make them more accurate and error-free.

KlearStack Solutions for Handwriting Recognition

KlearStack is the proud creator of a state-of-the-art optical character recognition software which completely changes the traditional notions about such applications. With an artificial intelligence backed methodology, KlearStack OCR emerges as a highly accurate handwritten character recognition software. Therefore, any handwritten document whatsoever can be converted into digital usable forms without compromising the accuracy with KlearStack’s OCR offering.

Ashutosh Saitwal
Ashutosh Saitwal

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.