Paper to paperless; The rise of Optical Character Recognition (OCR)

Ashutosh Saitwal
Ashutosh Saitwal

Founder CEO - KlearStack AI

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The biggest challenge for paperless routes is transferring archives to digital media. For a long time, the only way to communicate information from a printed document was to snail-mail it, but it could take forever. A more efficient method is Optical Character Recognition (OCR). This is the software used to convert scanned images of printed or handwritten text into machine-readable text. This is the way your company can profit from it.

To know more about what OCR is and how it is being widely leveraged, let us deep dive on to explore OCR in detail.


What is OCR?

Optical Character Recognition (OCR) is a technology that is used in businesses for automating data extraction from written or printed text from a document or image file and then converting the text from extracted data into machine readable form for data processing like editing or searching.


Evolution of the Optical Character Recognition (OCR)

OCR was first renowned as telegraph. Historically, companies were filming financial records on microfilm which was great in principle, but it was almost impossible to get a particular record off the reel of film quickly. To overcome this, pattern recognition was created with the help of projectors which helped in automating data recording by transforming existing technology.

Since then, OCR technology has grown rapidly and companies around the world have relied on OCR technology to reduce the hassle of converting and extracting data from paper documents. For ages, OCR has been considered a tool that helps in converting documents into interpretable and extractable data, however, digital documents serve a far more crucial purpose in today’s business environment.

OCR now leverages AI and ML where it offers greater flexibility by eliminating dependence on template recognition and continuously trains the algorithms on all documents for data extraction and create valuable insights for businesses.


How does OCR work?

OCR has evolved to optimize and automate business processes, where it digitizes records, improves accessibility while enhancing security. Enterprises can benefit from OCR, given its capability to increase operational efficiency and accuracy while improving data utility.

The working of OCR can be divided into three steps mentioned below:

  1. Scanning of the Document: While scanning the document, it should be correctly aligned. Horizontal and vertical alignment of the document’s text will improve the efficiency of the process. Scanning is not required in case the file is already in digital form like JPEG, PNG or PDF.
  2. Refining the image with software: Using the software, the elements of the document are refined where edges of alphabets are made smooth. It isolates and removes artifacts, dust particles and imperfection.
  3. Binarization: Binarization makes it easy to recognize the fonts and helps to differentiate text from the background. It will align the text and convert the colored text or grey shades to black and white only.
  4. Character Identification: The next step is to figure out the characters that are on the page. There are some basic forms of OCR that compare the pixels of the scanned alphabets to an existing font’s database and identify the closest match. The highly advanced forms of OCR break down each character into constituent elements to match the physical feature and actual letter.
  5. Ensures accuracy: OCR software can reduce more errors by taking the help of an internal dictionary to cross-check and ensure the accuracy.
  6. Produces editable digital text file: Fully searchable, digital file is produced that can be edited and utilized for further data interpretation and analysis.

Common uses of OCR:

  1. OCR in Healthcare: We scan, search and store patients’ medical histories that can contain the reports like X-rays, CT scan, medical history, hospital records and insurance payment details. OCR has streamlined the nature of workflow and has reduced manual administration.
  2. OCR in Banking: OCR helps to advance the transaction security and risk management by accurately extracting the data from KYC, checks, mortgage, loan documents, pay slips. It extracts the data from the ATMs improving the security and accuracy in the process.
  3. OCR for Logistics: For a long time, data entry was done manually, OCR enabled the automated data entry by allowing the authorities to identify inaccuracies in shipping documents. This helped in making the process faster and more accurate. Stakeholders find it difficult to extract the right information, OCR helps in extracting and validating the data from PDF copies and further trigger them as EDI messages to all relevant stakeholders. This makes the workflow automated and also improves the process flow and lessens the errors produced by humans.
  4. OCR for Legal: This industry deals with lots of paperwork which is why there is a dire need of OCR technology to help digitize handwritten notes, affidavits, judgments, statements and wills using OCR technology by the legal firms.
  5. OCR in E-Discovery and Online Investigation: OCR has a very important role to play in e-Discovery and online investigation. OCR software identifies and converts the text character from physical contracts, or typed letters, or JPEGs of photographed documents. You can now simply type your query into the search bar and all the references can be spotted. This has increased the pace of the discovery process and has also lowered the cost at the same time as time-consuming human review is not required. The digital information can be instantly searched for keywords, names and dates. OCR software cuts the time it takes to conduct an online investigation, and also allows investigators to massively expand the scope.

Which company should you choose for OCR application?

KlearStack is an AI based platform that has the most advanced and powerful Optical Character Recognition application for your businesses that can collect  data accurately from documents of several types. This OCR application by KlearStack uses ML algorithms, natural language processing and computer vision that efficiently detect errors and has self-learning capabilities which interpret the data and create practicable insights. OCR application by OCR has been already in use and has benefited many businesses in different sectors like banking, hospitality, insurance, finance, etc.To know more about our plans, and to take a free demo of the KlearStack OCR application, contact us today.


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