How to Leverage OCR for Smart Text Extraction in a DMS

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Here is a workplace scenario you might be all too aware of – Brian, the head of accounts, has taken a parental leave and cannot be reached on his cellphone. Meanwhile an important client you onboarded few months ago is waiting in the conference room to discuss minor issues in the purchase order. Your assistant is rummaging through different hard drives to find their invoice, and the only information that you remember is ‘the client works in solar.’

Now picture this – Brian, the head of accounts, is on a parental leave, and the ‘client who works in solar’ is waiting for you in the conference room. You need the purchasing order now, except instead of using traditional filing systems, your company uses a Document Management System like dox2U that is powered by OCR to provide Smart Text Extraction. What changed?

With Smart Text Extraction through a DMS like dox2U, all you needed was a keyword like “solar” to find the relevant purchasing order amidst thousand others, saving you from wasting your time anxiously hunting around for the information you need.

Companies, be it small startups or big corporations, regularly produce a ton of sensitive documents that need filing on an everyday basis. These documents can be invoices, ID cards, receipts, purchase orders, insurance policies, financial statements, legal documents, annual reports, etc. Without a reliable document management system, your company can get into legal and financial troubles.

What is OCR Smart Text Extraction?

Before OCR, it was fairly common to manually type out page after page of textual documents like purchasing orders or invoices. Manual data entry was slow and in-accurate. Optical Character Recognition, simply known as OCR, provided a much quicker and more secure alternative by leveraging patterns and using AI for character recognition, enabling document text extraction by capturing text from any complex, semi-structured or unstructured document.

Some of the earliest works in OCR were pioneered by Raymond Kurzweil, an American computer scientist involved in technologies in the early 1970s such as optical character recognition, text-to-speech synthesis, speech recognition technology, and electronic keyboard instruments.

OCR has come a long way since its inception in the early 1970s in both speed and accuracy, and the ability to automate complex text extraction workflows means scanned documents can retain their structure and be converted to workable digital formats after undergoing extraction. As you can imagine this brings huge benefits to industries dealing with forms and printed documents. Infact, most corporations today use OCR and Smart Text Extraction to quickly process large volumes of data and cut costs on manual errors.

How does OCR Smart Text Extraction Work?

OCR smart text extraction process is essentially a two-step process which involves analyzing the document’s textual structure and then processing the characters within the documents through certain algorithms. Here’s a detailed breakdown of the Smart Text Extraction process for documents.

Step #1

OCR program first needs to analyze the structure of the document image which requires it to:

Identify area of the text
Identify lines of text
Identity spacing between the words and sorts of document elements

Step #2

Once it has identified the characters, they are rendered to a Bitmap which defines the display space and the color for each pixel or “bit” in the display space. The characters can then be processed by any number of algorithms. The most common algorithm used in OCR are:

Pattern Recognition involves first training a computer with a very large set of known characters. With the learned understanding of what any imaginable variation of every character may look like, it’s just a matter of comparing the identified character with the closest matching pair.
Feature Analysis relies on the characteristics of each character; it looks at details like how many lines a character has, whether any of these lines intersect and how they intersect etc. In contrast to a standardized process followed by pattern recognition, feature analysis is a more rule-based process that requires a deeper understanding of characters on the part of the developer.

OCR combined with AI has proved to be a winning combination. By analyzing broader contextual and linguistic patterns, Artificial Intelligence is able to correct some mistakes that may slip through the cracks from OCR performance.

Benefits of OCR Smart Text Extraction in Document Management

A DMS (document management system) that incorporates an OCR has several workflow advantages to its users. Also, OCR-powered Text Extraction is not limited to creating a paperless office, but can be extended to all sorts of academic, business and social purposes.

Leading OCR systems like dox2U also offer added functionality of ICR (Intelligent Character Recognition) which can intelligently recognize handwriting in documents, in addition to the basic function of converting documents from static, analog formats to workable digital documents.

OCR can be used for the following purposes:

To convert text to speech
To convert PDF (portable document format) to word processor files for editing
To edit and fill out PDF forms
To edit PDF file size
To mark and annotate PDF files
To extract, rotate and cut pdf pages
To create digital signatures
To add hyperlinks and bookmarks to pdf documents

How to use OCR Smart Text Extraction for your Business?

Businesses can apply OCR tools dox2U text extraction for multiple purposes. Some of these include:

Table Extraction: dox2U text extraction tool removes the need for manual data entry and copying, as you can extract tables from any documents and download them as Excel files.
Smart Tagging: dox2U’s Text Extraction can read through content of a document and automatically assign metadata tags to the doc based on the content
Key Value Pair identification: This text extraction feature helps you process forms and invoices. It identifies a “Label: value” format in documents and extracts that information for you. For instance, say there’s an invoice that has “Invoice Number: 23456789”, this docx2U feature would allow the system to automatically detect that the Invoice Number for this invoice is 23456789 and then take relevant actions on it like include the info as tags.
Eligibility Check: This feature employs OCR and the key value pair identification functionalities to read through documents and determine eligibilities (think of like bank loan processing forms used to determine eligibility for loans or admission eligibility based on transcripts submitted to an Education firm)

Highlights:

Manual data entry can be slow, in-accurate, and vulnerable to piracy threats
Scanned documents are static, usually in PDFs or image formats
OCR turns the image or PDF into a workable digital format
OCR lets you detect text from scanned documents with relevant keywords
OCR text extraction is a DMS tool which helps capture text from various documents
Some SaaS companies like dox2U offer unique text extraction capabilities like handwriting detection, eligibility check, smart tagging, etc.
Leading OCRs like dox2U don’t store your private data in an unencrypted format

FAQs

What OCR means?

Optical Character Recognition or simply known as OCR is a document text extraction tool in document management system which uses pattern recognition and feature analysis to capture text from any complex, semi-structured or unstructured document. allows for a quicker and more secure alternative to document text extraction

What is an example of OCR?

If you are looking for advanced OCR programs that also offer ICR (including Handwriting recognition) and added enhanced capabilities, dox2u is a great choice. Other basic OCR programs include One Note by Microsoft, Google Keep and an open-source OCR program called Tesseract.

How is OCR different from a scanner?

When you scan a document through a scanner, it does not offer you the ability to search, select or copy/paste text from that document. Scanned documents, which are usually a PDF or an image, are static and analog. In contrast, when you use dox2U OCR, it not only turns the image or PDF into a workable digital format but also lets you search through any document for any text using keywords.

How to extract text from an image using OCR?

Just upload the document you want to scan on dox2U and it automatically sends the document for text extraction.
Once the document text is extracted, you can search for any part of the text using related keywords. This utility applies to both scanned PDFs and text images.

Is Online OCR safe?

Yes, top quality OCRs like dox2U don’t store your private data in an unencrypted format. It simply acts as a mediator between your data and their text extraction engine. Everything is encrypted in transit and at rest. Your data is for your eyes only.

How to Leverage OCR for Smart Text Extraction in a Document Management System?