Paper documents still play an important role in today’s digital world. Businesses have mountains of paper documents, ranging from old invoices to customer and vendor contracts. The information in these documents is vital, which means digitizing them and adding them to modern IT systems is crucial. But there’s an issue: scanning images of these documents is not the same as to extract text from them.
Why is this important?
Because the value of the papers lies in the text within.
OCR, which is an acronym for Optical Character Recognition, is a technology that’s built to solve this issue. In this article, we’ll dive into the world of OCR technology and explain how it can help businesses with their document scanning and storage.
What is OCR?
OCR is a type of artificial intelligence (AI) technology that enables computers to read text in scanned files and images. The best way to understand what OCR software can do is by exploring examples, so let’s dive right into one.
Let’s say there’s an important document in front of you, and you need to add the information from it to your digital project management system. You might use a mobile app or an office printer/scanner to take a few images of the documents. Depending on how you scan or photograph this document, you’ll end up with one of many file formats like JPEGs/JPGs, PNGs, BMPs, and TIFFs.
Sometimes, you might use tools like Adobe Acrobat Pro or a cloud-based file converter to convert scanned images into a PDF document. But can you guess what the issue with this process is? You’re only scanning the image of the document, not the information that’s in it.
That means even if you scan a document with handwritten text, you’ll probably have to retype it into Microsoft Word, PowerPoint, or whatever online tools you use. With one or two text documents, this might not seem like a hassle. When you’re dealing with a few hundred or a few thousand text documents, this becomes a nightmare.
What OCR software does is make images of text readable. It can turn scanned PDF files into searchable PDFs and extract editable text from image files and scanned documents. OCR tools can completely change the game for companies.
By the end of this decade, the OCR industry is set to reach almost $33 billion. Since OCR has piqued curiosity across sectors, the question that many have is “how does OCR work?”
How does OCR work?
In this section, we’ll explore how OCR engines function. The best way to do so is by breaking down what OCR tools do into small steps:
Step 1: Image Capture
The OCR workflow begins with an image, such as PNG, JPEG, or TIFF, or any other format. Images are fed into OCR tools from various sources. These include regular office scanners, mobile apps, or cloud-based storage services like Dropbox. Once an OCR tool has an image, it’s time for processing to begin.
Step 2: Image Processing
The OCR image processing phase, sometimes also known as the preprocessing step, isn’t as complicated as it sounds. Basically, this step involves cleaning up scanned documents and images to make the text stand out. Typical processes in this stage include deskewing, noise reduction, despeckling, and adjusting brightness and contrast to enhance the legibility of the text.
Step 3: Text Recognition
Once OCR tools clean up scanned documents and images, the next step involves identifying text. Again, while this may sound complicated, it just involves mapping fonts and identifying languages.
This process is typically powered by some form of AI or machine learning (ML) algorithms. Essentially, the OCR software cross-analyzes the lines and patterns found in the image with pre-existing databases to identify words and letters.
This is basically how an OCR tool identifies specific words or distinguishes languages. Besides multiple languages, this is also how an OCR tool navigates documents with different fonts.
Step 4: Text Output
In this step, the OCR engine discerns the actual text in the document. Whether you’re working with scans of old printed documents, handwritten forms, or any other type of digital document, the OCR tool identifies the written text. This is the step when images and scanned documents are made editable and searchable.
Once this step is complete, you can pretty much copy and paste any line of text from the document, even if it’s handwritten. Want to translate, edit, rewrite, or integrate into data entry workflows? This OCR step makes that possible.
Step 5: Postprocessing
In this last and final step of the OCR pipeline, text is made ready to use in different ways. In some cases, it’s saved in some form of text document or even an editable PDF file. If you have specific document management systems or other applications you want to feed this text into, most of the top OCR services can make that happen.
And there you have it: a 5-step OCR workflow that completely streamlines the process of deriving text from images and scanned documents.
What are the Different Types of OCR Scanning?
There are a few different OCR variations for organizations to choose from. There’s no single “best OCR type” out there. Instead, businesses need to select the type of OCR they want depending on their use cases. And that’s what’s really important to remember: a large healthcare organization’s OCR needs will be significantly different from those of a small or medium-sized business in a different field.
Now, let’s get into the main types of OCR:
Simple OCR
This rudimentary form of OCR can identify text from documents and images that feature printed characters. Most books, pamphlets, and corporate documents should work with this type of OCR.
As you might expect, high-quality documents and commonly used fonts will work best in this context. Documents with handwritten scribbles and atypical layouts might require advanced types of OCR.
OCR + Layout Recognition
This type of OCR extends into the design and layout of documents. The technology is helpful to identify and map tables, columns, rows, headings, and subheadings. They’re particularly effective at keeping the structural logic of a document intact through the entire OCR lifecycle.
Optical Mark Recognition (OMR)
Some might say OMR isn’t quite the same as OCR, but they’re definitely in the same family. OMR is integral to a comprehensive OCR process because it focuses on identifying marks and symbols within images and documents—things like logos, checkboxes, and symbols.
Intelligent Character Recognition (ICR)
Now we’re getting into more advanced OCR territory. ICR excels at handling the most complex use cases, a typical example being the ability to understand handwritten texts and more intricate symbols. This type of process relies more heavily on AI and ML because it essentially attempts to think about and read a text file like how a human would.
OCR Use Cases
So far, we’ve learned about what OCR is, what the average OCR workflow looks like, and the different types of OCR. Now, let’s shift our focus to how businesses can use OCR.
Below are a few common OCR use cases:
Making Scanned Documents Editable
If you’re taking a photo with your mobile phone of a document, and you want to select and edit text from that document, OCR has you covered.
Streamlining Data Entry Processes: OCR can be a valuable part of data entry processes, especially if the optical character recognition software you’re using can integrate with existing data entry workflows and automate text sharing.
Editing PDF Documents
Often, individuals and teams become frustrated because PDF documents contain outdated or incorrect information that needs to be corrected. OCR fixes that common point by allowing teams to edit details, fix typos, and update provisions.
Translating Scanned Documents
Many businesses need to translate documents, especially if their clients or suppliers operate overseas. OCR is great for translating scanned documents. Let’s say you want some English contracts translated into Portuguese or French—OCR tools can analyze documents and do that for you.
Digitizing Financial Documents
Finance teams experience significant stress and anxiety dealing with a multitude of receipts, invoices, reimbursement requests, and bills. OCR tools are excellent for digitizing this crucial data, which is especially useful for companies that want to store this data in cloud-based systems.
Besides these common OCR use cases, businesses in certain industries may have unique OCR requirements. For example, schools and educational institutions might want to scan worksheets and exam papers and make their contents editable. Law firms may need to digitize historical contracts and records and save that information in modern IT systems.
Retail companies may need to add information from bills and receipts into their data entry infrastructure. And healthcare companies can use OCR to digitize medical forms, test results, and prescriptions into both frontend and backend systems.
The Advantages of Using OCR Technologies
Let’s sign off by looking at the wondrous ways OCR can transform how organizations deal with a vast amount of paper documents in a digital world. Below are the top OCR benefits:
Cost Savings
Handling tons of paperwork isn’t easy or cheap. By digitizing documents into searchable and editable formats, OCR significantly brings down paper storage requirements and associated costs.
Streamlined Data Entry
Manually entering data or data entry can be frustrating and difficult for enterprise teams. Also, they’re often a hive of human errors. OCR streamlines and automates data entry processes by optimally weaving in data from images and scanned documents.
Automation-Driven Productivity
Imagine the amount of time employees spend on retyping paper documents and other data entry processes. OCR removes all of those time-consuming hassles.
Multi-Format Compatibility: Juggling files in dozens of formats is technically challenging. It’s also a process that kills productivity. Since OCR can derive text from multiple kinds of formats and transform them into easily usable digital text documents, the managed challenges posed by disparate file formats vanish.
Accessibility
OCR can detect and standardize a vast amount of information from scanned documents and images, enabling access for employees who previously (for various reasons) might not have been able to review, view, or use those materials. In a nutshell, OCR democratizes access to enterprise documents.
Happier Employees
Dealing with thousands of paper documents can cause significant lulls in productivity and morale. Since OCR can streamline and automate previously laborious processes, it offers a considerable boost to enterprise teams.
Without a doubt, no matter what kind of business you run, OCR can help make document management a hundred times easier.
Conclusion
OCR technology is beneficial for enterprises because it removes all the historical hassles associated with document management. Crucially, it also allows businesses to unlock the full value of text information in older paper documents. For companies dealing with multi-format documents, OCR makes it easy to transform them into searchable text.
Every industry in the world can benefit from OCR, and there are many new OCR innovations and advancements on the horizon. Navigating OCR alone is possible, but not always easy. Therefore, businesses that need a hand should consider working with experienced managed service providers (MSPs) & document management specialists who have deep OCR expertise and skills.
The bottom line? OCR is here to stay, and enterprises that use it can reap a plethora of measurable benefits.
