OCR

What is OCR?

OCR stands for Optical Character Recognition. It is a technology that converts text from scanned images or machine-printed (typed) text into editable, searchable data. Think of a scanned paper invoice, a PDF you receive via email, or even a photo of a document. To a computer, this is initially nothing more than a collection of pixels. OCR ensures that those pixels are transformed into usable information.

In practice, this means that numbers, letters, and punctuation marks are automatically recognized and—in the case of invoices—forwarded to your invoice processing system and/or ERP system. It’s no coincidence that OCR is also referred to as “scan & recognize” or “scan & capture.”

OCR plays a crucial role in digitizing information and automating document processing workflows, such as the invoice processing workflow. Without OCR, this is a labor-intensive task, especially as your organization grows and the number of invoices increases. OCR makes it possible to process invoices faster, more efficiently, and with less risk of errors.

How does OCR work?

You have an invoice. On paper, as a PDF, or perhaps as an image. To you, it’s clear: amounts, vendor, invoice number—it’s all there. To a computer? Just a picture—nothing more than a collection of pixels. And that’s not very useful, unless you use a tool like OCR. OCR goes through a series of steps to turn pixels into usable data:

Step 1: Capture the image

The OCR process begins by creating an image of the document, usually by scanning it or taking a photo of it.

Step 2: Preprocessing

During preprocessing, the image quality is improved. This includes reducing noise, enhancing contrast, and straightening crooked pages.

Step 3: Text recognition

Smart algorithms look for patterns that resemble letters, numbers, and symbols. Modern OCR software also uses machine learning to continuously improve this process.

Step 4: Data Extraction

The recognized characters are combined into words, sentences, and paragraphs. This creates a machine-readable version of your document.

The result?

A file you can search. Text information is stored in a hidden layer within the scanned image, so the file remains searchable while preserving the original’s appearance.

But keep in mind: OCR isn’t magic. The quality of the scan, the font, and the document’s formatting determine how well the recognition works. And handwriting? That remains a challenge, just as it can be for the naked eye.

Applications of OCR

OCR technology has a wide range of applications. We’ve been using it for years as a tool in the purchase-to-pay process, but it’s also suitable for other processes:

Document digitization

Overflowing archives? Stacks of paper contracts? OCR makes them searchable and digital. Say goodbye to those dusty archive folders.

Automation of data entry

Invoices, receipts, forms, and really any other document containing data you need to process; OCR extracts the data and prepares it for processing. Less manual work, fewer errors.

Accessibility

Converting printed or handwritten text into readable digital text or speech. For people with visual impairments, OCR makes a world of difference.

Searching and analyzing

OCR makes documents searchable. This is handy when you don’t want to read through an entire document just to find that one piece of information.

Mobile applications

OCR is built into apps that let you scan business cards, translate text, or extract information from a photo. Our expense report app also uses OCR to automatically process photos of receipts.

Banking and finance

In the financial sector and in financial processes, OCR is used to process checks, invoices, and other financial documents—all to increase speed and accuracy.

OCR Software: what options are available?

OCR software comes in many varieties, with differences in price, speed, functionality, and accuracy. A few options:

Freeware—Simple but limited. Usually suitable for one page at a time, and the output is limited to, for example, only TXT or DOC formats.
Desktop OCR—For small volumes. This often still requires manual steps during conversion.
Batch or server OCR—For larger volumes. This software processes entire folders of documents, in various file formats and languages, into exact copies in a format of your choice.

What should you look for when choosing OCR software?

Recognition accuracy
Language support
Speed and batch processing
Output file formats (Word, Excel, PDF, eBook, etc.)
Ease of use
OCR speed and support for multi-core CPUs
Advanced PDF encryption or compression

Important to know: No OCR tool can guarantee 100% accuracy. Documents with complex layouts, unusual fonts, or variable text orientations can pose challenges. Scan settings, fonts, and document quality also play a major role. A good scan (300 dpi, black and white) makes all the difference.

OCR & invoice processing: how does it work?

You receive invoices, for example, as PDFs via email. To the invoice processing software, that PDF is nothing more than an image. The software can do very little with it. Of course, you don’t want to retype everything.

OCR for invoice processing generally involves three steps:

You scan paper invoices manually, while PDFs and other digital invoices are automatically scanned from an email inbox.
After scanning, the data on the invoices is read and recognized by the OCR software.
The invoices are then forwarded to your invoice processing software for further processing, where as much information as possible is filled in automatically. This includes:
- Header data such as invoice number, invoice date, net, gross, and VAT amounts.
- Line-level data such as quantity, price per unit, line total, and description.

To make the best use of OCR in the invoice processing workflow, create templates. These templates tell the OCR software where information is located, and the software then searches for that information in those specific locations.

Keep in mind, however, that as soon as a supplier changes the layout of their invoices, you’ll need to re-specify where the information is located.

Intelligent Document Processing (IDP): the smart successor to OCR

A lot has changed since the advent of OCR; technology never stands still. Intelligent Document Processing (IDP) is the next step in document processing. While OCR primarily recognizes text, IDP goes further. It combines OCR with AI and machine learning. This makes it less reliant on templates and enables it to handle variable document layouts. Where IDP really makes a difference is that it understands text—it grasps the context.

What does that mean in practice?

Greater flexibility: IDP learns from your documents and adapts accordingly.
Fewer manual corrections: smart algorithms recognize patterns, even when a document is structured differently.

IDP is a very interesting option for organizations that need more flexibility than OCR can ever provide.

E-invoicing: the alternative

OCR is convenient, IDP is smarter, but neither is the end of the line. E-invoicing takes it a few steps further. No scans, no recognition—just structured data right away. Invoices arrive in a standard format such as XML or UBL and can be processed without any intermediate steps.

So why isn’t e-invoicing standard everywhere yet?

Suppliers must cooperate
There are many different standards that need to be converted to the standard your organization uses
This requires agreements and, sometimes, system adjustments.

Still, e-invoicing is the direction many organizations are moving in. Partly due to legislation, but hopefully mainly because of the benefits: less manual work, greater control, and increased speed.

What’s the best choice for your organization?

Do you still receive a lot of paper invoices or PDFs? Then OCR is a logical next step. It can save you a significant amount of manual work. But if you’re ready for the next phase, consider e-invoicing. It offers more than just time savings—it provides insight, compliance, and control.

And then there’s Intelligent Document Processing (IDP). It combines scanning and recognition technology with AI, so you aren’t dependent on templates and can better handle variable document layouts. For organizations that want to look beyond OCR, this is an interesting development.

OCR